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IC 9161 



Bureau of Mines Information Circular/1987 



Causes of Coal Miner Absenteeism 



By Robert H. Peters and Robert F. Randolph 



*m± 



UNITED STATES DEPARTMENT OF THE INTERIOR 



Information Circular 9161 



Causes of Coal Miner Absenteeism 



By Robert H. Peters and Robert F. Randolph 



UNITED STATES DEPARTMENT OF THE INTERIOR 
Donald Paul Hodel, Secretary 

BUREAU OF MINES 

David S. Brown, Acting Director 




^ 






A^ 



\ 



4> 



0' 



Library of Congress Cataloging in Publication Data: 



Peters, Robert H. 

Causes of coal miner absenteeism. 

(Information circular ; 9161) 

Bibliography: p. 32-35. 

Supt. of Docs, no.: I 28:27: 9161. 

1. Absenteeism (Labor) -United States. 2. Coal miners -United States. I. Randolph, 
Robert F. II. Title. III. Series: Information circular (United States. Bureau of Mines) ; 9161. 



TN295.U4 [HD5119.M615U6] 622 s [331.25'98] 87-600232 



CONTENTS 

Page 

Abstract 1 

Introduction 

Review of literature on miners' absenteeism 3 

Effects of miners' absenteeism 3 

Effects of absenteeism on safety 4 

Effects of absenteeism on productivity 4 

Causes of miners' absenteeism 5 

Research on causes of absenteeism among nonmining employees 7 

Personal characteristics 

Safety 9 

Health 9 

Unionization 10 

Work-related attitudes 10 

Job involvement 11 

Distributive justice 12 

Incentive programs 12 

Economic and job market conditions 13 

Attendance norms 13 

A model of the causes of miners' absenteeism 14 

Definition of variables 14 

Relationships between variables 15 

Perceived ability to attend 15 

Attendance motivation 15 

Overall job satisfaction 16 

Job involvement 17 

Distributive justice 18 

Absence control system permissiveness 18 

Desire to avoid loss of income 18 

At tendance norms 19 

Personal values 19 

Methods of data collection 20 

Sample 20 

Interviews 21 

Presentation of findings 21 

Individual variables 21 

Absenteeism 21 

Perceived ability to attend 22 

Transportation problems 25 

Age and illness 26 

Safety 26 

Attendance motivation 26 

Overall job satisfaction 26 

Job involvement 27 

Distributive justice. 28 

Absence control system permissiveness 28 

Desire to avoid loss of income 28 

Attendance norms 28 

Personal values 29 

Entire multivariate absenteeism model 29 

Discussion 29 

References 32 

Appendix. — Interview guide for miners. 36 



ii 



ILLUSTRATION 

Page 

1. Absenteeism model 14 

TABLES 

1. Breakdown of mine employees by job title 20 

2. Operational definitions of dependent (absenteeism) variables 22 

3. Operational definitions of independent variables 23 

4. Correlations of independent variables with absenteeism measures 25 

5. Regression models of nine absenteeism variables 30 





UNIT OF MEASURE ABBREVIATIONS USED IN THIS REPORT 


°F 


degree Fahrenheit pet percent 


min 


minute yr year 



CAUSES OF COAL MINER ABSENTEEISM 

By Robert H. Peters 1 and Robert F. Randolph 1 



ABSTRACT 

This Bureau of Mines report describes several significant problems as- 
sociated with absenteeism among underground coal miners. The vast em- 
pirical literature on employee absenteeism is reviewed, and a conceptual 
model of the factors that cause absenteeism among miners is presented. 
Portions of this model were empirically tested by performing correla- 
tional and multiple regression analyses on data collected from a group 
of 64 underground coal miners. The results of these tests are presented 
and discussed. 



' Research psychologist, Pittsburgh Research Center, Bureau of Mines, Bruce ton, PA, 



INTRODUCTION 



(82) claimed, "no 

has an absenteeism 

with coal mining, 

In 1980, Adkins 



Although estimates of the rate of ab- 
senteeism in the mining industry vary, 
most sources suggest that it is high rel- 
ative to the rate in other industries. 
Based on attendance data collected in May 
1978 and May 1980, the U.S. Bureau of 
Labor Statistics reported that, among all 
U.S. nonf arming industries, mining was 
the highest in terms of the proportion of 
hours lost to absences ( 75 , _7_8). 2 Taylor 
(75) notes, "The proportion of worker 
hours lost to absences in mining (5.1 
pet) was substantially higher than the 
corresponding total for the goods- 
producing sector as a whole (3.5 pet)." 3 
In 1976, Wilkinson 
other U.S. industry 
rate that compares 
which averages 12 pet. 
(2^) claimed, "the industry wide rate for 
U.S. underground coal mines has been run- 
ning at 10 to 15 pet for the past several 
years. For certain problem shifts, no- 
tably midnight on weekends, rates as high 
as 20 to 30 pet are not uncommon." 

An analysis of absence data presented 
by Goodman (21) reveals the following 
statistics concerning absence rates dur- 
ing 1982 at 11 relatively large under- 
ground coal mines with unionized labor: 
Total absenteeism across these 11 mines 
averaged 12.1 pet. 4 This total is com- 
posed of sanctioned absences (5.8 pet), 

2 Underlined numbers in parentheses re- 
fer to items in the list of references 
preceding the appendix. 

3 This rate was calculated as (number of 
hours absent/number of hours usually 
worked) x 100. However, absences result- 
ing from vacations, holidays, industrial 
disputes, or weather conditions were 
excluded. 

4 This rate was calculated as (total 
days absent/number of days scheduled to 
work) x 100. Unlike the Bureau of Labor 
Statistics study, Goodman includes gradu- 
ated vacation days in the numerator. He 
defines absences as any day when the mine 
was scheduled to operate, but the indi- 
vidual did not come to work. 



nonsanctioned absences (2.2 pet), and 
absences due to sickness and injury (4.1 
pet). 

Given current high rates of unemploy- 
ment in the mining industry, absence 
rates in the mid-1980' s are probably not 
so high as they were in the preceding 
decade. The U.S. Bureau of Labor Statis- 
tics May 1985 survey ( 77 ) found that ab- 
senteeism in the mining industry was 3.6 
pet. Although this rate is lower than 
the rates for mining reported in 1978 and 
1980, mining was still substantially 
higher than the overall average (2.5 pet) 
for goods-producing industries in 1985. 
Although the problem is not so widespread 
today as it once was, it still exists and 
will continue to haunt the mining indus- 
try from time to time until mine managers 
learn better methods for controlling it. 
Absenteeism can be expensive. At the 
national level, Steers and Rhodes (73) 
estimated the cost of absenteeism in the 
United States for 1983 to be about $30 
billion. Gandz and Mikalachki U8) esti- 
mated the annual costs of absenteeism in 
Canada to be about $8 billion. 

A 1980 survey by the Bureau of National 
Affairs (10) suggests what absenteeism 
can cost a single company: 

A small southern manufacturer re- 
ported that for the year 1980, the 
total paid absences of a group of 
310 hourly and nonexempt salaried 
employees cost the company approxi- 
mately $76,500. Of this total, 
paid sick time was $64,000; paid 
funeral leave was $3,500; paid jury 
duty was $700; paid personal time 
was $8,300. 1980 unpaid absence 
amounted to $70,000 in manhours 
lost from work. A large southern 
manufacturer reported that one hour 
of absence is equivalent to 2 1/2 
hours production cost increases. A 
small central manufacturer reported 
that to cover for absent employees, 
20 extra employees are needed on 
the payroll at a cost of over 
$30,000 each. 



A study by Moch and Fitzgibbons (53) 
suggests what absenteeism can cost a sin- 
gle department. They estimated that un- 
anticipated absenteeism in one department 
of a medium-sized food packaging plant 
resulted in a loss of $60, 075 annually in 
product wastage. The authors point out 
that the total costs of absenteeism at 
this plant are much greater than this 
figure because the plant has 29 other 
product lines, and because absenteeism 
results in several types of significant 
costs other than product wastage. 

Although there appear to be no publish- 
ed estimates of the cost of absenteeism 
in the mining industry, one can safely 
assume that, based on the estimated rates 
of absenteeism, the costs are signifi- 
cant. In 1976, the labor relations vice 
president for one of the largest coal 
companies reported that his company was 
carrying an extra 5 pet of manpower to 
allow them to cope with absenteeism (82). 

It is inevitable that members of under- 
ground coal mining crews will occasion- 
ally be absent. Sometimes the crew will 
work without a replacement, but usually 
someone is assigned to fill in for the 
missing miner. In either case, produc- 
tion and safety problems become more 
likely. Temporary replacements for regu- 
lar crew members often are relatively un- 
familiar with the habits of the people 
who work in the crew and with the physi- 
cal conditions and equipment in the 
section. 

Because they are unfamiliar with key 
aspects of their work environment, tem- 
porary replacements often either do 



things (or fail to do things) that can 
reduce productivity and contribute to 
accidents. This problem is especially 
important in underground coal mining 
because the work environment is very 
hazardous, and because the tasks perform- 
ed by miners are very interdependent. 
The entire production process can be 
stopped if any one of several critical 
activities is not performed properly. 

To keep attendance as high as possible, 
it is important to understand as much as 
possible about what causes miners to be 
absent. Understanding the primary causes 
of absenteeism is a prerequisite for 
deciding which of several strategies will 
be most effective for maintaining a high 
level of attendance. Therefore, the 
Bureau of Mines conducted the research 
study presented in this report primarily 
to learn more about the reasons for coal 
miners' absences. Based on prior studies 
of absenteeism (discussed in a later sec- 
tion), predictions were made concerning 
factors that might be likely to influence 
miners ' rates of absenteeism. These pre- 
dictions were empirically tested on a 
sample of 64 underground coal miners. 
Miners' absenteeism rates during a recent 
12-month period were used as the crite- 
rion variable, and data on miners' demo- 
graphic characteristics and attitudes 
about their work were used as predictors. 
The mine where this study took place 
is located in western Virginia. All 
individuals from whom data were obtained 
were nonsupervisory personnel who work 
underground. 



REVIEW OF LITERATURE ON MINERS' ABSENTEEISM 



The literature on miners' absenteeism 
can be divided into that which considers 
absenteeism to be the cause of other con- 
ditions or events, and that which con- 
siders absenteeism to be the consequence 
of other conditions or events. ^ This 

^Although it remains a distinct possi- 
bility, very few authors have viewed ab- 
senteeism as reciprocally related to 
other variables. 



section discusses the literature pertain- 
ing to each of these two viewpoints. 

EFFECTS OF MINERS' ABSENTEEISM 

Most of the literature dealing with 
miners' absenteeism as a causal variable 
focuses on the effects that absenteeism 
has on mine safety and productivitry. 



Effects of Absenteeism on Safety 



Effects of Absenteeism on Productivity 



The Theodore Barry report (76) notes 
that absenteeism leads to "short-crew" 
sections, with crew members forced into 
unfamiliar operations and tasks: 

In short-crew situations, section 
foremen often request that one or 
more crew members from the previous 
shift "double-back", i.e., work a 
second consecutive shift. Fatigue 
is the natural result of a 16-hour 
period of hard physical activity, 
and fatigue and accidents are high- 
ly correlated in any industrial 
activity. 

Adkins (2) also refers to the negative 
effect of absenteeism on safety: 

Having to shift job assignments, 
work places and sometimes whole 
crews at the mine portal as the man 
trip is loaded is an obvious admin- 
istration headache, devastating to 
crew and supervisor morale and det- 
rimental to mine safety. Upon 
these consequences of absenteeism 
there is consensus. 

Wilkinson (82) cites several mining 
company and union officials who have 
claimed that miners' absenteeism produces 
unsafe working conditions. The United 
Mine Workers has even tried sending union 
representatives out to the homes of poor 
attenders to discuss the importance of 
good attendance. 

The first empirical study of the ef- 
fects of miners' absenteeism on accident 
rates was performed by Goodman (21 ). 
Data were collected from a sample of min- 
ers at 19 underground coal mines. The 
data consisted of the mines' daily atten- 
dance records, accident records, and de- 
tailed interviews with approximately 50 
miners from each mine. It was found that 
crews with poor job attendance consis- 
tently experience slightly more accidents 
than other crews. Goodman attributes the 
greater incidence of accidents in these 
crews to the tendency for replacement 
workers to be relatively unfamiliar with 
their temporary jobs. 



It is generally acknowledged that ab- 
senteeism adversely affects a mine opera- 
tion's productivity. However, as Adkins 
(2) points out, it is not necessarily 
easy to estimate accurately how much pro- 
ductivity would increase if absenteeism 
could be reduced by X pet. Adkins ' main 
conclusion regarding the relationship be- 
tween miners' absenteeism and productivi- 
ty is that the relationship is complex 
and subject to the intervention or over- 
riding influence of other variables: 

The relationship between productiv- 
ity and absenteeism is mine specif- 
ic and idiosyncratic. The reason 
the relationship is hard to deter- 
mine is because, under any given 
set of physical constraints, pro- 
ductivity and absenteeism are both 
subject to other human performance 
elements that act independently of 
the physical environment. Absen- 
teeism is only one of several 
"people problems" elements that im- 
pact productivity. 

In describing the processes by which 
absenteeism influences productivity, 
Adkins notes, 

First of all absent workers simply 
don't produce much coal. In more 
indirect paths one can see that ab- 
senteeism can both increase safety 
problems and decrease the general 
skill level of the crews. Deterio- 
rating skill levels lower produc- 
tion and increase maintenance and 
down-time problems. Absenteeism 
leads to labor/management relations 
problems, frequently arising from 
attempts to discipline absent 
workers, which in turn lowers the 
productivity of both labor and 
management. 

Goodman and Leyden (23) provide empiri- 
cal evidence concerning the effect of 
crew size on productivity. They analyzed 
data from 81 mining crews at 6 under- 
ground coal mines, using the number of 
tons of coal removed by a mining crew 



during a shift as the criterion variable. 
After using multiple regression to sta- 
tistically partial out the effects of 
other factors, crew size consistently em- 
erged as a statistically significant var- 
iable in accounting for variations in the 
criterion variable. This strongly sug- 
gests that absenteeism that results in 
crews with fewer than the normal number 
of persons significantly reduces 
productivity. 

An empirical study of various depart- 
ments within a food processing plant by 
Moch and Fitzgibbons (53) revealed that 
absenteeism and work group efficiency are 
negatively associated only (1) when pro- 
duction processes are not highly automat- 
ed, and (2) when the absences are not 
anticipated (and therefore cannot be 
planned for in advance). They argue that 
automation may significantly reduce the 
negative consequences of unanticipated 
absenteeism because it reduces the criti- 
cal functions performed by employees to 
those that can be carried out by anyone 
with minimal ability and familiarity with 
the job. Because underground mining cur- 
rently cannot be automated to the point 
that employees are more or less inter- 
changeable, these findings suggest that 
when unanticipated absences occur and an 
experienced substitute cannot be found, 
the absence will lower the crew's level 
of productivity. 

In conclusion, it appears that miners' 
absenteeism is generally considered to be 
important cause of accidents and low pro- 
ductivity. However, with the exception of 
Goodman (21) and Goodman and Leyden (23), 
there appears to be very little empirical 
evidence concerning these assumptions. 

CAUSES OF MINERS' ABSENTEEISM 

As was true about research on the con- 
sequences of miners' absenteeism, there 
appears to be considerable speculation 
about the causes of miners' absenteeism, 
but little empirical evidence other than 
that provided by Goodman (21). This sec- 
tion summarizes the literature on the 
causes of miners ' absenteeism. 

Adkins (2) identifies downtime as an 
important determinant of miners ' absentee 
rates: 



Several miners said, in essence, 
that going to work was much more 
enjoyable when they felt they could 
produce coal and noted that if they 
got to the section to find it down 
their morale would fall and they 
would be more likely to consider 
"going out." This reaction is 
partly but not solely because they 
might have to do "dead work." Many 
felt even more discouraged when 
they faced a shift of doing 
nothing. 

Adkins also suggests that job satisfac- 
tion is an important determinant of min- 
ers' attendance. He argues that miners' 
job satisfaction is largely determined by 
intrinsic and extrinsic rewards, job in- 
volvement (one's affective and intellec- 
tual ties to the job), peer relations, 
and supervisor-subordinate relations. 

Although Adkins argues that good peer 
relations can lead to better attendance, 
he cautions that — 

Peer pressure to attend work does 
not, however, seem to be evident in 
the coal industry even though the 
additional hazard created by ab- 
sence is generally recognized. 
There seems to be a countervailing 
group norm that recognizes a min- 
er's right to "take a day off" now 
and then, totally at the individu- 
al's discretion. 

Wilkinson (82) expresses a similar 
point of view about the relative inef- 
fectiveness of peer pressure to attend. 
He quotes the vice president for adminis- 
tration at Island Creek Coal Co. : 

We used to be able to rely on the 
cohesiveness of the crew to keep 
down absenteeism, but because of 
job-posting, the crew structure 
isn't as strong as it used to be. 
There's no longer the question of 
letting the crew down. 

Adkins argues that the primary de- 
terminants of good relations between 
supervisors and their crew are communi- 
cation and trust: 



Of all complaints in industry, no 
single one is heard more than the 
complaint about lack, of comnunica- 
tion. The comments "no one ever 
tells me anything" or "no one ever 
listens to me" are all too common. 
This feeling of isolation and of an 
inability to receive or deliver in- 
formation important to the satis- 
factory performance of one's job is 
a prime element of job dissatisfac- 
tion. The second component, trust, 
comes as a result of exercising 
honesty, fairness and respect in 
interpersonal dealings in the work 
place. 

As has already been mentioned, job 
posting has been identified as an impor- 
tant contributor to miners' absenteeism. 
However, the Theodore Barry report (76) 
identifies a somewhat different process 
by which job posting leads to absentee- 
ism. The report argues that eliminating 
posting would reduce the disproportionate 
number of new men on swing and midnight 
shifts and decrease absenteeism caused by 
the nondesirability of swing and midnight 
shift hours, particularly for younger 
men. 

A labor relations manager for Peabody 
Coal Co.'s western mines has identified 
the mine's distance from various types of 
human services as an important determi- 
nant of absenteeism (82) : 

In the case of some of the western 
mines, the sites are so remote that 
miners have to drive 150 miles to 
get to a bank, doctor, barber, etc. 
They take days off to do this. 

Studies by Hedja, Smola, and Masek (29) 
and Goodman (21) both suggest that ill- 
nesses are an important cause of miners' 
absences. Hedja 's group ( 29 ) has con- 
ducted a well-designed study on the ef- 
fects of two types of interventions on 
the prevention of coal miners' illnesses. 
During the winter months of 1971-74, ex- 
perimental groups of Czechoslovakian coal 
miners were given daily doses of vitamin 
C by their employer. Records were kept 
of the number of injuries and the number 



and duration of illnesses suffered by 
miners in control groups, who received no 
vitamin C, and in the experimental 
groups. In later stages of the study, 
one experimental group received influenza 
vaccinations in addition to the vitamin 
C. 

A significantly lower proportion of 
miners had absence due to illness in the 
experimental groups than in the control 
groups, and the average duration of such 
absence in the experimental groups was 
markedly shorter. It was also observed 
that the incidence of illness in the 
group who received vaccinations and vi- 
tamin C was lower than the incidence of 
illnesses in the group who received vac- 
cinations but did not receive vitamin C. 
It was also found that the incidence of 
injuries in the experimental groups was 
45 pet lower than that observed in the 
control group. 

In summary, there is some empirical 
evidence to support the claim that vita- 
min C and influenza vaccinations are ef- 
fective in reducing miners' absenteeism. 

As part of Goodman's (21) study of 
miners' absenteeism, miners were asked to 
indicate what causes them to miss work. 
The reason cited most frequently was ill- 
ness. Although this methodology for 
determining the causes of miners' ab- 
sences has some distinct limitations, the 
results of several studies conducted in 
other types of industries (using various 
research techniques) also strongly sug- 
gest that illnesses are a very important 
cause of absences. These studies are 
discussed in a later section. 

Goodman's (22) empirical evaluation of 
the effects of an autonomous mining crew 
structure suggests that the degree to 
which miners are allowed to participate 
in decisions affecting their job is a 
significant determinant of absenteeism. 
(The primary effect of an autonomous crew 
structure is to increase miners' oppor- 
tunity to participate in decisions af- 
fecting their job.) He found that, in 
comparison with control group crews (who 
kept the traditional pattern of central- 
ized decision making), absenteeism was 
reduced to a significantly lower level in 
the autonomous mining crews. 



Goodman's ( 21 ) more recent empirical 
study of coal miners' absenteeism reveals 
the following concerning the types of 
factors that appear to contribute to 
miners' absenteeism: 

1. Illnesses and injuries are the most 
commonly cited causes of absence. 

2. Off-the-job activities that miners 
need or want to do (e.g., family, hunt- 
ing) are also commonly cited. 

3. Negative job factors that might 
cause miners to avoid work are NOT fre- 
quently mentioned sources of absences. 

4. Demographic factors such as age 
have a strong effect on attendance, but 
the nature of the effect differs from 
mine to mine. 

5. Miners holding down another job 
are consistently absent more than their 
coworkers. 

6. An organization's absence control 
policy and the degree to which that po- 
licy is consistently implemented within 
the workforce is a significant determi- 
nant of attendance. 

7. Most miners do not feel highly 
pressured to produce — but those who do 
have higher absence rates. 

8. Most miners report that they would 
rather have more time off than more 
money. This suggests that the desire for 
time away from work is one of the more 
important forces contributing to absen- 
teeism. 

In summary, the following is a list of 
the variables that have been cited in the 



literature as potential causes of miners' 
absenteeism: 

Excessive downtime 

Low job satisfaction or high 
dissatisfaction 

Low extrinsic rewards 

Low job involvement 

Poor peer relations 

Poor supervisor-subordinate relations 

Job posting 

Extreme distances between mine and 
essential human services 

Illnesses 

Centralized decision making 

Desire or need to engage in off-the-job 
activities 

Holding a second job 

Inconsistent implementation of the 
absence control policy 

Extremely high production pressures 

High desire for time off relative to 
desire for money 



RESEARCH ON CAUSES OF ABSENTEEISM AMONG NONMINING EMPLOYEES 



Much research has been performed on the 
causes of employee absenteeism. This 
section attempts to characterize the 
findings from this body of literature in 
a concise manner. Only a few studies are 
described in detail. The main findings 
with regard to the following classes of 
causal variables are presented: personal 
characteristics, safety, health, unioni- 
zation, work-related attitudes, job 
involvement, distributive justice, in- 
centive programs, economic and job market 
factors, and attendance norms. 



PERSONAL CHARACTERISTICS 

Personal factors constitute a category 
of variables relating the characteristics 
of individuals to absence behavior. 
While numerous studies have been pub- 
lished, few consistent findings have 
emerged. In particular, absenteeism has 
been generally found to be positively 
related to family size (55), health pro- 
blems ( 11 , 41 , 63), poor previous at- 
tendance (9, 2§.» 54. 83), and age C6_6). 



A further influence on attendance is 
the personal value system of individuals 
(68). Some research suggests that a 
strong personal work ethic is closely re- 
lated to attendance ( 17 , 20 , 35). Pre- 
sumably, those individuals who feel 
morally obligated to work follow through 
in the form of actual attendance. 

Hill and Trist (32-33) argue that some 
employees possess an "undealt-with uncon- 
scious hostility towards authority," and 
that this trait is responsible for a high 
rate of both absenteeism and job-related 
injuries. They reviewed the accident and 
absence records of a group of 289 men who 
joined the Park Gate Iron and Steel Co. 
Ltd. during 1947 and were still employed 
there after 4 yr. During this period 200 
remained free of accidents, while 89 had 
sustained one or more. 

These two groups, of 200 and of 89 men 
respectively, were then compared with re- 
gard to their total number of absences. 
The first hypothesis was that accidents 
may be used as a means of withdrawal from 
the work situation, and their occurrence 
therefore is likely to be influenced by 
the quality of the person's relationship 
with his employing authority. The with- 
drawal hypothesis was supported by the 
finding that those sustaining accidents 
incurred significantly more absences (due 
to reasons other than accidents) than 
those who had remained free of accidents. 

A second hypothesis, the sanctioning 
hypothesis, states that accidents will 
tend to be most associated with the least 
sanctioned forms of absences and least 
associated with the most sanctioned 
forms. The authors state, 

This hypothesis links the sociolog- 
ical concept of legitimacy of so- 
cial behavior to the psychological 
attitude of the individual towards 
authority — ultimately to his inter- 
nal willingness to accept responsi- 
bility for himself. An accident is 
something for which an individual 
does not usually accept responsi- 
bility. Industrial accidents may 
therefore be expected to be related 
to other forms of absence where the 
individual does not accept respon- 
sibility for his behavior towards 



his employing authority, into which 

undealt-with unconscious hostility 

towards authority in his personal- 
ity may be projected. 

The two groups of 200 and 89 men were 
therefore also compared in terms of the 
following types of absences: 

1. Leave with permission granted 
beforehand. 

2. Leave where permission is not asked 
beforehand, but where the absence is rat- 
ified on return to work. 

3. Certified sickness. 

4. Uncertified sickness. 

5. Unsanctioned absences. 

A significant association was found 
between the incurring of accidents and 
unsanctioned absences (type 5). Also 
significant in their association with 
accidents were the retrospectively 
sanctioned absences (type 2-4), though 
in lesser degree. Prospectively sanc- 
tioned absences (type 1), on the other 
hand, were negatively associated: those 
who were able to accept most responsibil- 
ity in taking matters up with the appro- 
priate representative of their employing 
authority — those who got permission 
first — were those who tended most to 
avoid accidents. In summary, Hill and 
Trist provide some rather indirect, but 
provocative, empirical evidence to sup- 
port the notion that absenteeism and ac- 
cidents are caused by an employee's 
undealt-with unconscious hostility toward 
authority. However, not everyone agrees 
with this explanation. Like Hill and 
Trist (32), Verhaegen, Strubbe, Vonck and 
Abeele (79) also found a significant re- 
lationship between absence and accident 
rates. However, unlike Hill and Trist, 
they do not attribute the source of these 
absences and accidents to unconscious as- 
pects of one's personality. They argue 
that both absenteeism and job-related ac- 
cidents reflect an overall negative at- 
titude that some employees have toward 
their employer — an attitude that these 
employees are quite conscious of. 

An interesting area of concern with re- 
spect to personal factors is the topic of 
the personal value of nonwork activities. 



Johns and Nicholson (36) discuss this 
subject at length, suggesting that some 
absence may be attributable to the value 
indivduals place on their "outside activ- 
ities." For instance, Morgan and Herman 
(54) found that absence was related to 
anticipated achievement of off-the-job 
social outcomes and leisure time. On the 
basis of such findings, Johns and Nichol- 
son (36) argue that "attendance patterns 
may reflect an attempt to balance the 
quantity and quality of time spent in 
various endeavors." Similarly, Young- 
blood (84) found that the value of lei- 
sure time was significantly related to 
total hours of absence. Youngblood con- 
cluded that "the results generally sup- 
ported the view that absenteeism is a 
function of motivation processes extant 
in both the work and nonwork domains." 

SAFETY 

A commonly cited assumption is that 
absenteeism leads to more dangerous work- 
ing conditions. However, Allen (_3) sug- 
gests that the reverse is also true: 
Dangerous working conditions can cause 
high absenteeism, turnover, and other 
forms of withdrawal. He argues that not 
only do hazardous working conditions 
cause absences directly, i.e. , through 
lost-time injuries, such conditions also 
cause high absenteeism indirectly — 
employees wish to avoid their workplace 
because it is perceived as a threat to 
their safety and health. 

As part of his doctoral dissertation 
research at Harvard, Allen analyzed data 
from 1,022 employees interviewed for the 
1972-73 Michigan Quality of Employment 
Survey (includes employees across several 
different industries and occupations). 
Multiple regression analyses of these 
data revealed that absenteeism incidence 
rates are negatively related to (1) the 
employee's marginal earnings, (2) the 
perceived degree of occupational safety 
at the job, and (3) the flexibility of 
the work schedule, i.e., absenteeism is 
significantly higher in jobs with low 
wages, high perceived risk of occupation- 
al illness or injury, and inflexible work 
schedules. 



The self-evaluated danger variable co- 
efficient was quite sizable and statisti- 
cally significant (p <0. 01). 6 Allen's 
data suggest that workers who feel they 
are exposed to dangerous or unhealthy 
working conditions have a daily absence 
rate that is about two percentage points 
higher than the rate for other workers, 
i.e., about 50 pet higher than the aver- 
age 4-pct rate. Leigh (46) replicated 
this finding using data from 747 employ- 
ees interviewed for the 1973 Michigan 
Quality of Employment Survey, i.e., the 
self-evaluated danger variable was posi- 
tively associated with absenteeism at a 
statistically significant level (p 
<0. 05). These results complement Vis- 
cusi's ( 80 ) finding that the quit rate is 
positively related to the risk of occu- 
pational illness or injury across 
establishments. ^ 

HEALTH 

Illness is widely recognized as the 
most important cause of absenteeism (26- 
28 , 47 , 60), accounting for from one-half 
to two-thirds of all employee absence 
(51 ). In Goodman's (21 ) study, almost 
all miners cited illnesses and injuries 
as the most common cause of their 
absences. 

The recent literature on health locus 
of control beliefs has found that inter- 
nals (those who believe that health is 
substantially under one's own control 
through proper health habits) displayed 



6 The symbol "p" represents the proba- 
bility that no replicable effect exists 
given the observed data. Thus, if p is 
small, the measured effect is likely to 
represent a "real" and reproducible ef- 
fect. Measured effects that are large 
enough to result in values of p less than 
0.05 are commonly considered to be 
"statistically significant." 

'Allen cautions that cost-benefit ana- 
lyses of safety investments that do not 
consider the effects on absenteeism 
and turnover will underestimate the 
benefits. 



10 



more desirable self-care and provider 
care behaviors than did externals (those 
who believe that one's health is largely 
a function of luck or chance) ( 43 , 81). 
Because of their better health habits, it 
can be expected that internals would be 
less likely to be sick than externals and 
hence to have lower absenteeism. This 
was one of several hypotheses recently 
tested on a sample 190 employees of a 
medium-sized communication equipment man- 
ufacturing and distribution plant (38). 
When 10 independent variables were ex- 
amined for their ability to add unique 
variance to the prediction of absentee- 
ism, only health locus of control, prior 
absenteeism, and group cohesiveness were 
found to be significant. In summary, 
there is some empirical evidence to sup- 
port the claim that employees with an 
internal health locus of control have 
lower rates of absenteeism. As, the 
evidence is limited to a single study, 
future research should attempt to repli- 
cate this finding. 

UNIONIZATION 

Leigh (46) argues that through provid- 
ing a monopoly (high) wage, unions dis- 
courage absenteeism because the opportu- 
nity costs of missing work are relatively 
high. On the other hand, unions tend to 
provide more generous sick leave bene- 
fits, which often reduce the opportu- 
nity cost of missing work to zero. 
Leigh empirically tested a model of the 
effects of unionization on absenteeism 
using data from the 1973 Michigan Quality 
of Employment Survey. The survey util- 
ized a national probability sample of 
persons 16 yr old and older who were 
working for pay for 20 or more hours per 
week. The results of logit regressions, 
which provide statistical controls for 
human capital and demographic character- 
istics as well as working conditions, 
suggest that the net effect of unioni- 
zation is to encourage absence among blue 
collar workers (p <0.05), but not among 
white collar workers. Blue collar union 
members were absent roughly 2.6 pet more 
often than nonunion blue collar workers. 



WORK-RELATED ATTITUDES 

According to Steers and Rhodes (73) , 
overall job satisfaction, job involve- 
ment, organizational commitment, and 
several dimensions of job satisfaction 
(work itself, supervision, coworkers, 
pay, and promotion) have received the 
greatest research attention among the 
work-related attitudes as predictors of 
absence. They have identified 31 studies 
on overall job satisfaction, 9 studies on 
job involvement, 8 studies on organiza- 
tional commitment, 21 studies on satis- 
faction with work itself, 19 studies on 
satisfaction with supervision, 16 studies 
on coworker satisfaction, 18 studies on 
pay satisfaction, and 17 studies on pro- 
motion satisfaction. 

Job satisfaction is the degree to which 
individuals like their jobs (72). Virtu- 
ally all major reviews of the absenteeism 
literature have found consistently sig- 
nificant relationships between job dis- 
satisfaction and absenteeism. However, 
the associations found in these largely 
bivariate studies have not been particu- 
larly strong (48) and have been generally 
limited to measures of overall job satis- 
faction (65) and satisfaction with work 
(55). Nicholson, Brown, and Chadwick- 
Jones (57) have provided a frequently 
cited illustration of the serious diffi- 
culties researchers have encountered in 
their attempts to demonstrate that the 
various facets of satisfaction are major 
determinants of absenteeism. Their study 
failed to identify a demonstrably strong 
relationship between a good facet measure 
of satisfaction (modified Job Description 
Index, _72) and multiple measures of ab- 
sence, in a large sample of workers from 
16 separate organizations. However, 
Nicholson's conclusion that "the common 
view of absence as a pain-reductive re- 
sponse on the part of the worker to his 
work experience is naive, narrow, and 
empirically unsupportable" appears to be 
an overstatement. An alternative explan- 
ation for their findings is that, charac- 
teristic of research in this area, other 
important determinants of absence be- 
havior (such as the employee's ability to 



11 



attend) were omitted from their model. 
Herman (30) claims that work attitudes 
are important predictors of absences only 
when the absences are under the control 
of the employee — which is often not the 
case. 

To test this argument, Smith (71 ) exam- 
ined the relationship between the work 
attitudes and work attendance of two 
large groups of managerial employees on a 
specific day but at different locations — 
one where it had snowed the previous day 
and one where it had not. Since occa- 
sional absenteeism at the managerial 
level is not subject to financial penalty 
and is relatively free of social and 
work -group pressures, it represents be- 
havior that is generally free of social 
and work -group pressures, i.e., it repre- 
sents behavior that is generally under 
the control of the individual employee. 
Moreover, because the particular day in- 
vestigated in this study followed "an un- 
expected and severe snowstorm that great- 
ly hampered the city's transportation 
system" (71), employees had even more 
discretion over whether or not to attend. 
Absent employees probably expected that 
their superiors would understand that 
they had decided not to come to work due 
to the snowstorm, and would not fault 
them for being absent. The primary sam- 
ple of 3,010 employees was located at 
Sears headquarters in Chicago. The con- 
trol group was located at Sears' New York 
office. The results show significant re- 
lationships between six work-related at- 
titudes and attendance on the specific 
day studied. The snowstorm attendance in 
Chicago is significantly correlated with 
all six attitude measures and, in the 
case of three scales, is highly (1-pct 
level) significant (supervision, finan- 
cial rewards, and career future). In the 
New York sample, none of the correlations 
were significant. These results general- 
ly support Herman's (30) point of view 
that work attitudes do predict work- 
related behavior when such behavior is 
under the control of the employee. 

These findings suggest two important 
things about using job satisfaction to 
predict absenteeism: (1) Employees' job 



satisfaction is important in understand- 
ing absences only in instances when the 
employee has some control over whether or 
not to attend, and (2) it is important to 
determine employees' satisfaction with 
specific aspects of their job, because 
certain work aspects are significantly 
more highly correlated with attendance 
than others. 

McShane's (50) metaanalysis of the 
absenteeism-job satisfaction literature 
supports the assumption that employees 
who are dissatisfied with various aspects 
of their jobs are more likely to be ab- 
sent. In particular, the relationship 
was strongest for overall satisfaction 
and work (job content) satisfaction. 
Moreover, in contrast to previous reviews 
( 55 , 74), satisfaction with coworkers, 
pay, and supervision was also related to 
reduced absenteeism. However, satisfac- 
tion with promotions was uncorrelated 
with absenteeism. 

In summary, there appears to be a 
fairly consistent, modest, and inverse 
relationship between work-related atti- 
tudes and absenteeism. 

JOB INVOLVEMENT 

According to Kanungo (37) psychologists 
have defined job involvement in several 
different ways. Most definitions contain 
one or more of the following components: 
job involement is the extent to which 
(1) the employee's work is a central life 
interest, (2) the employee actively par- 
ticipates in his or her job, and/or 
(3) the employee perceives good job per- 
formance as central to his or her self- 
esteem and consistent with his or her 
self-concept. Bass (4) argues that in- 
volvement in one's job is determined by 
the presence of six conditions: oppor- 
tunity for making job decisions, the 
feeling that one is making important con- 
tributions to organizational success, and 
experience of personal success, personal 
achievement, self-determination, and 
personal autonomy in matters of setting 
one's own work pace. Lawler and Hall's 
(45) notion of job involvement is that 
"the more the job is seen to allow the 



12 



holder to influence what goes on, to be 
creative, and to use his skills and 
abilities, the more involved he will be 
in the job." As one might expect, the 
available empirical evidence concerning 
the effects of job involvement on absen- 
teeism suggests that highly involved 
workers exhibit significantly lower 
levels of absenteeism (6^, 9^, 13 , 24 , 61 , 
69). 

DISTRIBUTIVE JUSTICE 

Distributive justice is the degree to 
which rewards and punishments are related 
to performance inputs into the organiza- 
tion (34). This concept addresses the 
degree to which employees are rewarded 
fairly for their contributions and ef- 
forts on behalf of the organization. 
Several researchers have considered the 
perceived absence of distributive justice 
to be an important cause of employee ab- 
senteeism, e.g., Chadwick -Jones, Brown, 
and Nicholson, (12), Dittrich and Carrell 
(16), Gibson (19), Johns and Nicholson 
(36), March and Simon (49), and Patchen 
(61 ). However, this assumed relationship 
has been empirically tested by only a 
very small number of researchers, e.g., 
Dittrich and Carrell (16). 

INCENTIVE PROGRAMS . 

Three general types of incentive pro- 
grams have been used to reduce absentee- 
ism: positive reinforcement programs, 
negative sanctions programs, and mixed 
programs that used both positive and 
negative incentives. 

Positive reinforcement programs provide 
some reward for lower absenteeism. 
Steers and Rhodes' (73) review of re- 
search on these programs indicates that 
reinforcers such as bonuses, participa- 
tion in a lottery, participation in a 
poker hand, food credit reimbursement for 
unused sick leave, and desirable work 
schedules can lead to a reduction in ab- 
senteeism. While there are other pro- 
grams using positive reinforcement that 
did not lead to a reduction in absentee- 
ism, the majority of the empirical evi- 
dence supports the effectiveness of 
positive reinforcement programs. 



Programs based on negative sanctions 
are built around absentee control plans. 
Control plans usually specify stages, 
levels of absenteeism permitted, penal- 
ties, and continuous attendance necessary 
to work oneself off the absentee control 
plan. Basically these plans identify a 
series of stages of varying forms of 
punishment. For example, absenteeism at 
a particular level would lead to a warn- 
ing letter. Subsequent levels of absen- 
teeism would lead to a suspension. Con- 
tinued absenteeism would lead to 
dismissal. 

Despite the widespread use of manage- 
ment sanctions in business organizations 
(10), the evidence supporting their ef- 
fectiveness in attendance control is 
limited largely to anecdotal case 
studies — very little empirical research 
of acceptable quality has been performed. 
For example, Seatter (70) discussed an 
attendance control program based on rel- 
atively strict disciplinary measures im- 
plemented over a 5-yr period. While 
Seatter reported a major (and sustained) 
reduction in absence rates during the 
time period, it was impossible to separ- 
ate the program's effects from the multi- 
tude of exogenous variables that could 
have accounted for the improvement in 
attendance. 

According to Steers and Rhodes (73) and 
Baum (_5), the literature is characterized 
by divided opinions and conflicting find- 
ings concerning the efficacy of sanctions 
in reducing absenteeism. Much of the op- 
position to the use of sanctions is based 
on two grounds: (1) Behavior modifica- 
tion techniques based on positive rein- 
forcement of desired behaviors (coming to 
work regularly) are more suitable and 
effective in dealing with absenteeism, 
and (2) sanctions based on the use of 
disciplinary procedures (punishments) 
tend to produce undesirable side effects 
that are as objectionable as the behavior 
of primary interest. For example, 
Nicholson (56) found that rigorously 
enforced sanctions caused workers to 
resort to longer, medically related ab- 
sences to escape the consequences of the 
disciplinary system; the overall level of 
days lost was not changed by the "clamp- 
down." In contrast, a well-designed 



13 



empirical study by Baum (_5) found that 
the strict enforcement of an absence con- 
trol policy significantly reduced absen- 
teeism without causing any discernible 
change in either long-term illnesses or 
contractual absences. 

Several plans that include both posi- 
tive incentives for attendance and nega- 
tive sanctions for absence have been 
devised and empirically tested ( 25 , 39- 
40 , 42). These mixed-consequence plans 
were generally found to be quite effec- 
tive at reducing absenteeism. The design 
of these mixed plans varied considerably. 
Those who wish to find out the details of 
each of these plans are referred to the 
four articles cited above. 

ECONOMIC AND JOB MARKET CONDITIONS 

Economic and job-market conditions 
often place constraints on employees' 
ability to change jobs. As a result, in 
times of high unemployment, there may be 
increased pressure to maintain a good at- 
tendance record for fear of losing one's 
job. Evidence suggests that there is a 
close inverse relationship between 
changes in unemployment levels within a 
given geographic region and subsequent 
absence rates (_7-8> J^O* Moreover, as 
the threat of layoff becomes even greater 
(for example, when an employee's own 
employer begins layoffs), there may be an 
even stronger decrease of absenteeism (8, 
15). On the other hand, when an employee 
knows that he or she is to be laid off 
(as opposed to a knowledge that layoffs 
are taking place in general), the situa- 
tion is somewhat different. Specifi- 
cally, Owens (59 ) found that railway 
repair employees in a depressed industry 
who had been given notice of layoff 
because of shop closure had significantly 
higher absence rates prior to layoffs 
than a comparable group of employees who 
were not to be laid off. Owens suggests 
that, in addition to being a reflection 
of manifest anxiety, the increased absen- 
teeism allowed employees time to find new 
positions. However, Hershey ( 31 ) found 
no significant differences in absence 
rates between employees who were schedu- 
led for layoffs and employees not so 



scheduled. He argued that the subjects 
in his study were much in demand in the 
labor market and generally felt assured 
of finding suitable jobs. Steers and 
Rhodes (73) summarize the evidence con- 
cerning the influence of this set of 
factors as follows: 

When general economic conditions 
are deteriorating, absenteeism de- 
creases for several reasons. 
First, employees with poor atten- 
dance records may be among the 
first to be laid off. Second, re- 
maining employees may be less 
likely to be absent for fear of 
reprisal. However, when the 
individual employee is to be laid 
off, absence rates are apparently 
influenced by one's perceptions of 
his or her ability to find alter- 
nate employment. When such alter- 
natives are readily available, no 
effect of impending layoff on ab- 
senteeism is noted; when such 
alternatives are not readily avail- 
able, absence rates can be expected 
to increase as employees seek other 
employment. 

ATTENDANCE NORMS 

Although there has been very lttle em- 
pircal research on the influence that 
work-group norms have on absenteeism, 
several authors have suggested that such 
norms have an important effect; see, for 
example, Gibson (19 ) and Steers and 
Rhodes (74). Moreover, Lawler (44), in 
his job-attractiveness model of employee 
motivation, pointed out that members of 
highly cohesive groups often view coming 
to work to help one's coworkers as highly 
desirable. Johns and Nicholson ( 36 ) 
argue that "the net interactive effect of 
the normative forces that exist in the 
various relevant portions of employees' 
role sets" is of central importance in 
understanding absence behavior. In ad- 
dition to his or her coworkers, the 
employee's attitudes about the appropri- 
ateness of absences are also probably 
influenced by the expectations of close 
friends and relatives. 



14 



A MODEL OF THE CAUSES OF MINERS' ABSENTEEISM 



Using the findings from prior research 
on the absenteeism of miners and other 
types of employees, a conceptual model of 
the factors that produce absenteeism 
among miners was generated (fig* 1). 
Predictions regarding the direction of 
the association between the variables in 
the model are indicated by the symbols 
"+" or *'-". The remainder of this sec- 
tion contains definitions for each of 
the variables and an explanation for 
each hypothesized relationship between 
variables. 

DEFINITION OF VARIABLES 

Total absences (absenteeism definition 
1) — The total number of scheduled work 
days that the miner has failed to show up 
for work. 

Frequency of absences (absenteeism def- 
inition 2) — The total number of absence 
events, where an absence event is de- 
fined as any set of consecutive days of 



absence. For example, three consecutive 
days of absences would constitute a sin- 
gle absence event. 

Severity of absences (absenteeism def- 



inition 3)— The 



mean duration 
(Severity s 



absence event, 
absences/total frequency. ) 
Attendance motivation — The 
intend or want 



of the 
total 



degree to 
to attend 



which miners 
work. 

Perceived ability to attend — The degree 
to which miners perceive themselves able 
to attend work. 

Age — Number of years old. 

Health status — The degree to which min- 
ers are free from illness and disease. 

Job safety — The degree to which the 
miners' workplace is free of hazards. 

Satisfaction with safety — The degree to 
which miners are satisfied with their 
personal safety while at work. 

Satisfaction with coworkers — The degree 
to which miners view their coworkers as 
friendly and cooperative. 



Transportation problems 
Health status 
Safety- + 



Fear of 

underground 



Downtime- 
Shift 




S/W coworkers 

-S/W equipment 

S/W working conditions 
-S/W opportunities for social acts 

S/W advancement opportunities-, 

S/W job content 



S/W supervision closeness- 
S/W supervision fairness- 
S/W pay 



Control system permissiveness- 
Local unemployment rate — 
Kinship responsibility- 
Attendance norms- 



Personal work ethic 



Attendance 
motivation 



• Absence 



Desire to avoid 
income loss 



KEY 

♦ Positive association 
- Negative association 



FIGURE 1.— Absenteeism model. (S/W = Satisfaction with. The hypothesized relation between the variables "Shift" and 
"Satisfaction with opportunities for social acts" is that miners who work daytime shifts are more satisfied with their opportunities 
for participating in social activities than those who work other shifts.) 



15 



Satisfaction with equipment — The degree 
to which miners are satisfied with the 
quality of the equipment they work with. 

Satisfaction with working conditions — 
The degree to which miners like or dis- 
like the physical aspects of their work 
environment. 

Satisfaction with opportunities for 
family and social activity — The degree to 
which miners are satisfied with their op- 
portunities to interact with their family 
and friends. 

Satisfaction with career advancement 
opportunities — The degree to which miners 
are satisfied with the types of jobs they 
expect to have if they continue to work 
for their present employer. 

Satisfaction with job content — The de- 
gree to which miners like their work. 

Satisfaction with closeness of 

supervision — The degree to which miners 
perceive that their supervisor trusts 
them to do their work properly, allows 
them to set their own work pace, and 
gives them the freedom to choose how to 
do their job. 

Satisfaction with fairness off supervi- 
sion — The degree to which miners perceive 
that their supervisor allocates work as- 
signments, resources, and various non- 
monetary rewards and punishments in an 
equitable manner. 

Satisfaction with pay — The degree to 
which miners are satisfied with the 
amount of money or equivalents distri- 
buted in return for service. 

Overall job satisfaction — The degree to 
which miners like their jobs. 

Job involvement — The degree to which 
miners perceive that their job allows 
them to influence what goes on, to be 
creative, and to use their skills and 
abilities. 

Distributive justice — The degree to 
which miners perceive that the rewards 
(and punishments) they receive from their 
supervisor and employer are fair, given 
the level of their contributions to the 
organization. 

Absenteeism control system permissive- 
ness — The degree to which absenteeism is 
accepted by an organization, i.e. , em- 
ployees do not expect that frequent ab- 
sences will be punished by adverse 
consequences. 



Desire to avoid income loss — The min- 
er's desire to avoid having his or her 
pay reduced (for unexcused absences). 

Local job opportunities — The degree to 
which acceptable jobs with alternative 
employers are available. 

Kinship responsibility — The extent of 
the miner's financial responsibilities 
for supporting dependents. 

Attendance norms — The extent to which 
members of the miner's immediate work 
group, family, and friends view his or 
her absences negatively. 

Personal work ethic — The degree to 
which miners feel morally obligated to 
attend work. 

RELATIONSHIPS BETWEEN VARIABLES 

Working backwards through the model, it 
is hypothesized that asenteeism is nega- 
tively associated with both attendance 
motivation and perceived ability to 
attend. 

Perceived Ability To Attend 

Miners' ability to attend is obviously 
an important factor in actual attendance. 
However, perceived ability may be more 
important than actual ability. That is, 
a snowstorm or a bad cold may or may not 
limit one's ability to come to work. 
What is important is how the individual 
treats the event and how he or she inter- 
prets its impact on ability to attend; 
for example, given equivalent transporta- 
tion situations, some miners may report 
to work during a snowstorm while others 
may not. This is why the model contains 
a dotted line going from attendance moti- 
vation to perceived ability to attend. 
In addition to attendance motivation, 
other important determinants of perceived 
(and actual) ability to attend are 
transportation problems, illness, and 
injuries. 

Attendance Motivation 

The model identifies eight direct 
determinants of miners' attendance moti- 
vation: overall job satisfaction, in- 
cluding satisfaction with time for social 
activities; job involvement; distributive 



16 



justice; absence control system permis- 
siveness; desire to avoid income loss; 
attendance norms; and personal values. 
Each of these is discussed below. 

Overall Job Satisfaction 

Although many researchers have found 
that job satisfaction is related to at- 
tendance, Goodman's (21 ) study suggests 
that job satisfaction may not be an espe- 
cially good predictor of coal miners' at- 
tendance. The relationship between these 
two variables should be further investi- 
gated. Therefore, it is hypothesized 
that job satisfaction is positively re- 
lated to miners' attendance motivation. 
For practical as well as theoretical 
reasons, it would be valuable to know 
which specific facets of job satisfaction 
are most strongly related to absenteeism. 
Therefore, the following variables are 
also included: 

Satisfaction With Safety 

The psychological fears associated with 
underground mining are an important con- 
sideration. The possibility of death or 
severe harm from falling rock, entrap- 
ment, explosions, and inundation is like- 
ly to detract from underground miners' 
desire to attend work. In addition to 
variations between miners in terms of the 
magnitude of their inherent fears about 
working underground, another important 
determinant of the degree to which miners 
are satisfied with their safety is the 
degree to which the workplace is per- 
ceived to be free of hazards. Owing to 
the hazards associated with mining, safe- 
ty satisfaction is probably a more impor- 
tant predictor of overall job satisfac- 
tion for the mining industry than it is 
for most other industries. 

Satisfaction With Coworkers 

The work involved in underground mining 
is generally performed by small crews of 
approximately 10 or fewer people. These 
crews are physically isolated from one 
another. It is important that miners 
develop good relations with their co- 
workers because the work demands much 



coordination between crew members. This 
variable is considered a more important 
predictor of overall job satisfaction for 
miners than for employees in other 
industries. 

Satisfaction With Equipment 

Adkins has identified downtime as an 
important source of miners' dissatisfac- 
tion with work. He argues that miners 
become discouraged when frequent equip- 
ment problems force them to be idle for 
extended periods or cause them to perform 
"deadwork." This variable is probably a 
more important predictor of overall job 
satisfaction for miners than it is for 
employees in other industries. The un- 
comfortable nature of the underground 
environment makes it difficult for miners 
to find pleasant ways to pass extended 
periods of idle time. The amount of 
downtime is probably determined by the 
age and quality of the equipment and 
the amount of preventive maintenance 
performed. 

Satisfaction With Opportunities for 
Family and Social Activities 

A significant portion of the time most 
underground coal miners spend at work is 
during evening and night shifts. Because 
miners who work these shifts may have 
limited opportunities to do things with 
their family and friends, they may be 
especially likely to be absent from time 
to time so that they can take part in 
such activities. The rotating shifts 
used by some mining companies can also be 
disruptive to a miner's social life. 
Therefore, it is hypothesized that those 
who work nondaytime or rotating shifts 
(1) have lower levels of overall job 
satisfaction and (2) have lower levels of 
motivation to attend work. This is simi- 
lar to experience in other industries 
with evening and night shifts. 

Figure 1 shows a line leading directly 
from the variable Satisfaction with 
opportunities for social acts to the 
variable Attendance motivation . This is 
because, unlike the other "job satisfac- 
tion" variables, miners' Satisfaction 
with opportunities for social activities 



17 



Attendance motl- 
11 as indirectly, 
Overall satisfac- 
is hypothesized to 
luence on miners' 
than the other 
determinants of 
miners' overall job satisfaction. 



is thought to influence 
vation directly as we 
through its impact on 
tion. This variable 
have a more direct inf 
attendance motivation 
variables listed as 



Satisfaction With Conditions of Work 

The physical environment creates sev- 
eral types of discomfort for those who 
work underground. Conditions typically 
found in underground coal mines include 
darkness, high levels of noise and dust, 
dampness, temperatures, of about 50° F, 
and ceilings that are not high enough for 
employees to walk or stand in an upright 
position. While underground, miners 
usually do not have access to clean 
water, toilets, or many of the other 
"necessities" that employees in other 
industries take for granted. In addition 
to the physical discomforts caused by the 
underground environment, some miners also 
experience psychological discomfort due 
to feelings of being "closed in" and 
isolated from the world outside. These 
conditions suggest that physical aspects 
of the work environment may be an impor- 
tant source of overall job dissatisfac- 
tion for miners. 

Satisfaction With Job Content 

Jobs in underground mining vary in 
terms of the degree to which miners de- 
rive satisfaction from performing them. 
Some jobs are more challenging, more in- 
teresting, more dangerous, less repeti- 
tive, more free from supervision, or less 
physically demanding than others. Some 
require fewer skills and are perceived as 
less important than others. Miners' sat- 
isfaction or dissatisfaction with their 
job classification is determined by both 
the characteristics of the work and the 
characteristics of the individual. Sat- 
isfaction with job content reflects the 
degree to which the characteristics of a 
miner's work are congruent with the 
miner's interests, desires, and capabili- 
ties. Prior research suggests that this 



variable is significantly related to both 
absenteeism and turnover (52). 

Satisfaction With Supervision 

Two important elements of miners' job 
satisfaction are the degree to which they 
are free from close supervision and the 
degree to which they perceive that their 
supervisor treats them fairly. Goodman 
(22) has noted that miners exhibit strong 
preferences for behaving autonomously: 

Mining throughout the years has 
been a very autonomous activity 
and very likely the nature of the 
work has reinforced the miners' 
personal preference for work that 
is relatively free from close 
supervision. 

Given the apparent importance of this 
variable to coal miners, it is hypo- 
thesized to be a significant determinant 
of overall job satisfaction. 

For obvious reasons, it is expected 
that miners who do not feel that their 
supervisor treats them fairly will have 
lower levels of overall job satisfaction. 
Adkins (2) also cites fair treatment 
as an important determinant of miners' 
absenteeism. 

Satisfaction With Career Advancement 
Opportunities 

Promotion among underground miners us- 
ually implies moving into another non- 
managerial job that is somewhat higher 
paying and likely to be less physically 
demanding and perhaps more intrinsically 
satisfying (i.e., the work is perceived 
as more important and more interesting). 
It is hypothesized that miners' overall 
job satisfaction is heavily influenced by 
the degree to which they are satisfied 
that they can realize their career goals 
by staying with their present employer. 

Job Involvement 

Job involvement has been found to be 
positively related to attendance. Ac- 
cording to most definitions, the key 



18 



determinants of job involvement are as- 
pects of job content, supervision, and 
career advancement opportunities. To the 
extent that the job involves work that 
allows the miner to feel that he or she 
is making important contributions to the 
organization, to experience a sense of 
personal achievement, and to make use of 
his or her skills and abilities, the min- 
er will be involved in his or her job. 
To the extent that miners are supervised 
in such a way that they are typically al- 
lowed to influence what goes on at their 
work site, set their own work pace, ac- 
tively participate in decisions about 
their work, and use creativity in solving 
problems, they will be involved in their 
jobs. To the extent that miners perceive 
that their career advancement opportuni- 
ties with their current employer are good 
(i.e., that they are sufficiently com- 
petent and successful to be given the op- 
portunity to perform more important and 
more difficult jobs in the future), min- 
ers will be involved in their current 
jobs. Therefore, it is hypothesized that 
(1) miners' satisfaction with job con- 
tent, freedom from close supervision, and 
career advancement opportunities are all 
positively related to their job involve- 
ment and (2) the greater the miners' job 
involvement, the greater is their motiva- 
tion to attend work. 

Distributive Justice 

Equity theory, as originally proposed 
by Adams (O, considers employees' per- 
ceptions of fair treatment by their em- 
ployer to be a major determinant of their 
motivation to make contributions of time, 
energy, ingenuity, etc. , to their job. 
The theory holds that one way employees 
may respond to actual or perceived unfair 
treatment is to reduce their job contri- 
butions. One obvious way to accomplish 
this reduction is to attend work less 
often (assuming that no loss of pay re- 
sults). Therefore, it is hypothesized 
that a significant determinant of miners' 
attendance motivation is the extent to 
which they perceive that they are treated 



fairly by their employer, i.e., the 
degree to which distributive justice 
is perceived to exist in the employee- 
employer exchange. 8 

One important determinant of distribu- 
tive justice is miners' perceptions about 
the adequacy of their wages, benefits and 
other economic rewards their employer 
provides. Another important determinant 
is the degree to which miners perceive 
that their supervisor allocates work as- 
signments, resources, and various non- 
monetary rewards and punishments in an 
equitable manner. Therefore, it is hy- 
pothesized that miners' perceptions of 
distributive justice are determined by 
their satisfaction with their economic 
rewards and the degree to which they per- 
ceive that their supervisor treats them 
fairly. 

Absence Control System Permissiveness 

Absence control systems involve those 
policies and procedures used by the orga- 
nization to encourage attendance; permis- 
siveness in this context is the degree to 
which absenteeism is accepted by the or- 
ganization. An organization or subunit in 
which numerous casual absences result in 
few or no apparent adverse consequences 
would be highly permissive toward absen- 
teeism. Empirical support for the hy- 
pothesized direct causal relationship be- 
tween permissiveness and absenteeism has 
been reported by Seatter (70), Rhodes and 
Steers (67), Winkler (83), and Popp and 
Belohlav (64). Therefore, it is hypothe- 
sized that a high degree of permissive- 
ness of the mine's control system is 
positively associated with absenteeism. 

Desire to Avoid Loss of Income 

Miners differ in the extent to which 
they desire to avoid losing income. The 
strength of this desire is hypothesized 

^For a more extensive discussion of the 
employee-employer exchange and its impli- 
cations for employee motivation, see 
Pearce and Peters (62). 



19 



to be positively related to their atten- 
dance motivation. Two determinants of 
miners' desire to avoid income loss are 
the local unemployment rate and kinship 
responsibilities. 

Local Unemployment Rate 

Economic and job-market conditions 
often place constraints on employees' 
ability to change jobs. As a result, in 
times of high unemployment, there may be 
increased pressure to maintain a good at- 
tendance record for fear of losing one's 
job. As previously discussed, several 
studies have found an inverse relation- 
ship between changes in unemployment 
levels within a given geographical region 
and subsequent absence rates. Therefore, 
it is hypothesized that local unemploy- 
ment rates are positively related to 
miners' desire to avoid income loss and 
to attendance motivation. 

Kinship Responsibility 

Another determinant of miners' desire 
to avoid income loss is the degree to 
which they are responsible for supporting 
family members or other dependents. In 
contrast to single miners with fewer 
financial responsibilities, miners who 
must support a family are probably less 
willing to take the chance of losing some 
of their pay (or getting fired) because 
they take off work for reasons the com- 
pany considers unexcusable. Therefore, 
it is hypothesized that kinship respon- 
sibility is positively related to miners' 
desire to avoid income loss, and to 
attendance motivation. 

Attendance Norms 

As previously mentioned, prior research 
suggests that another important deter- 
minant of attendance motivation is the 
degree to which the immediate work group 
views one's absences from work nega- 
tively. Therefore, it is hypothesized 
that miners' attendance motivation is 
positively related to the degree to which 



their crew views absences among its mem- 
bers negatively. 9 Although it has not 
been formally tested, it would also seem 
likely that a miner's attendance motiva- 
tion is significantly affected by the 
norms of the miner's family, relatives, 
and close friends regarding the impor- 
tance of job attendance. 

Personal Values 

Finally, the miner's personal value 
system may be an important determinant of 
job attendance. As previously mentioned, 
prior research suggests that a strong 
personal work ethic is closely related to 
attendance. Therefore, it is hypothe- 
sized that miners' attendance motivation 
is positively related to the degree to 
which they have a strong personal work 
ethic. 

It is also important to consider per- 
sonal values concerning nonwork activi- 
ties. Some absence may be attributable 
to the value miners place on their non- 
work activities. In his study of the 
Rushton Mine, Goodman ( 22 ) found that, 
although they view their work as impor- 
tant, miners usually did not feel that 
their job was the central part of their 
life; home and other nonwork activities 
were more central. This observation sug- 
gests that the values miners place on 
nonwork interests (e.g., hunting, hob- 
bies, family activities) may be an 
important reason for some of their 
absences. 

This section has presented a conceptual 
model of the causes of coal miners' ab- 
senteeism. Although a large number of 
variables have been included in the 
model, not every factor that can influ- 
ence absences has been discussed. 
Rather, the variables included are in- 
tended to implicitly reflect the influ- 
ence of the unnamed variables. For 
instance, miners' experience has been 

^However, for various reasons it has 
been argued that the amount of peer group 
pressure on miners to attend work is min- 
imal (2, 76, 82). 



20 



frequently hypothesized to be important 
in determining absences. The current 
model implicitly includes the important 
aspects of experience in several expli- 
citly defined variables. Miners with 
more experience are less likely to be 
absent. However, the reasons for their 
lower absence rates probably stem pri- 
marily from two factors already included 
in the model, shift assignment and kin- 
ship responsibility. Miners with more 
experience are apt (1) to be more likely 
to work day shifts (which, as the model 
indicates, means that they will have more 
opportunities to participate in social 
activities than those who work other 



shifts) and (2) to be older and have 
greater kinship responsibilities (which, 
as the model indicates, means that their 
desire to avoid income loss will be 
greater than for younger miners with 
fewer financial responsibilities). The 
next step in this study was to collect 
data that could be used to begin assess- 
ing the degree to which the model 
actually accounts for variations in coal 
miners ' rates of absence. Only by col- 
lecting and analyzing data on the actual 
behavior of coal miners can one begin to 
realize the model's limitations and see 
how it can be improved. 



METHODS OF DATA COLLECTION 



SAMPLE 

Absenteeism data were collected for a 
12-month period beginning July 1985 for 
103 coal mine employees. These employees 
represent 95 pet of the nonsupervisory 
personnel who work underground at the 
mine where this study was conducted. 
This mine has been in operation for about 
20 yr. It is one of several mines in the 
area that are owned by a large mining 
company. The coal from this mine is used 
to supply a major electric power company 
in a nearby State. 

The mine operates three nonrotating 
shifts. The day and evening shifts are 
devoted to producing coal, and the night 
shift is devoted to maintenance activi- 
ties. A layoff occurred at this mine 
shortly before the study began. Conse- 
quently, all the miners in this study had 
been working for their current employer 
for at least 13 yr. However, given that 
widespread layoffs in the coal industry 
occurred during the mid-1980s, this 
mine's older workforce is presently 
typical of many mines in the industry. 

Coal was being extracted using the 
advancing room and pillar method and con- 
tinuous mining machinery. The mine's 
employees were covered by the current 
United Mine Workers of America contract. 
This contract specified that miners are 



allowed 4 floating days, 5 personal or 
sick days, and 11 holidays in addition to 
their graduated vacation days. The 
company's policy was to pay employees for 
any of these contract days that they did 
not take, and to give letters of commen- 
dation to those with good attendance 
records at the end of each year. Al- 
though unexcused absences occurred now 
and then, neither management nor labor 
perceived absenteeism to be a significant 
problem at this mine. Table 1 breaks 

TABLE 1. - Breakdown of mine 
employees by job title 

Number 

Job title of 

miners 

Belt operator 10 

Brattice worker 2 

Electrician 10 

Face worker 2 

Fireboss 2 

General inside laborer 3 

Miner helper 4 

Miner operator 4 

Motor operator 4 

Reset worker 1 

Roof bolter operator 12 

Shuttle car operator 8 

Track worker 2 

Total 64 



21 



down the total sample of mine employees 
by job title. The average miner was 44 
yr old, had worked as a miner for 20 yr, 
was responsible for three dependents, and 
lived 21 miles from work. All persons in 
this sample worked underground on a 
full-time basis. The sample did not in- 
clude cleaning plant personnel or any 
other type of employee who worked above- 
ground. 

INTERVIEWS 

Interviews were conducted underground, 
somewhere near the miners' worksites. 
All interviews were conducted in private. 



Miners were assured that their responses 
would be held in strict confidence 
and were told that their participa- 
tion was completely voluntary. Inter- 
views required approximately 25 min to 
complete. 

Data were collected with a structured 
interview guide. (See appendix. ) Inter- 
viewers asked questions concerning the 
following issues: (1) satisfaction with 
various job aspects, (2) details about 
one's most recent absence, (3) activities 
miners engage in when they are absent 
from work, and (4) several other details 
including age, martial status, number of 
dependents, and number of miles the miner 
must drive to get to the mine. 



PRESENTATION OF FINDINGS 



The relationships of individual vari- 
ables will be discussed first, followed 
by the test of the entire hypothesized 
absenteeism model. 

INDIVIDUAL VARIABLES 

The overall rate of absenteeism among 
the sample of miners studied was 17 pet. 
This was computed as follows: 

Total absence rate = total days absent 

number of days 
scheduled to work 

Total days absent includes all types of 
recorded absences, everything from con- 
tract days to unexcused days. Number of 
days scheduled refers to the number of 
days the mine was scheduled to operate — 
this does not include the holidays and 
vacation days during which the mine was 
not scheduled to operate. The overall 
rate of absences (17 pet) includes 12 pet 
that were due to illnesses and injuries, 
5 pet that were days allowed by the con- 
tract (e.g., graduated vacation days), 
and a small fraction of a percent that 
were considered unexcused absences. 

For the purposes of statistical anal- 
ysis, the variables discussed in the 
previous sections were operationally 



defined 1 in terms of items in the data 
collection instruments. (See appendix.) 
These definitions are discussed below: 

Absenteeism 

A total of nine variables were con- 
structed to characterize different types 
of attendance behavior. Following the 
categories used by Goodman (21), absences 
were characterized as either voluntary, 
semivoluntary, or involuntary: 

1. Voluntary absence , V - These were 
absences characterized as discretionary, 
or contract days, or discretionary holi- 
days, graduated vacation days, and mis- 
cellaneous paid absences. 

2. Semivoluntary absence , SV - These 
were excused unpaid absences, and unex- 
cused absences (AWOL's). While these may 
reflect some volition, they clearly are 
more costly to the individual and less 
desirable. This is a fuzzy category, 

1 ^An operational definition is one that 
specifies the meaning of the concept by 
denoting the measuring operations. Oper- 
ational definitions specify the measuring 
operations used to identify phenomena, 
e.g., defining intelligence as one's 
score on an IQ test. 



22 



but seems Intuitively distinct from cate- 
gory 1. 

3. Involuntary absence , IV - These 
were absences categorized as on-the-job 
injuries, illnesses, and off-the-job in- 
juries. There may be some argument 
here, particularly as to illness. Some 
authors have argued for short-term ill- 
ness as often attitudinal in origin and 
possibly less costly than an AWOL ab- 
sence. There is not sufficient informa- 
tion from the mine as to the validity of 
these concerns. To the extent this cate- 
gory does not generate shorter spells of 
absence, this may be a real threat. 
However, such an absence is still more 
costly than a voluntary absence, so that 
contrast of this category to the volun- 
tary category should still be testable. 

The mining company's coding system was 
used to assign miners' absences to Good- 
man's three categories. The mapping be- 
tween the mine's categories and Goodman's 
is shown in table 2. The operational 
definitions of the dependent variables 
are described in table 3. 

For each of these three types of ab- 
sences, three summary indices were 

TABLE 2. - Operational definitions of 
dependent (absenteeism) variables 



Category 
Voluntary (V)., 



Semi voluntary (SV) 



Involuntary (IV).. 



Company's code 

Authorized. 

Floating vacation. 

Graduated vacation. 

Personal day (paid). 

Refused work. 

Leave of absence. 

Suspended. 

Unauthorized. 

Unexplained. 

Bereavement. 

Jury duty. 

Military leave. 

No work available. 

Non occupational 
illness. 

Non occupational 
injury. 

Occupational ill- 
ness. 

Occupational injury, 

Strike. 



computed to characterize miners' absence 
behavior over the entire year of data 
collection. The conceptual meaning and 
method of calculating the indices (total, 
frequency, and severity of absences) was 
described earlier. A few of the miners 
were not employed during the entire year, 
so the indices were normalized by the 
total number of days each miner could 
have come to work. Hence, a miner who 
worked only half of the year and was 
absent one-tenth of the year would 
receive a total absences index of 0.05 
(0.5 x 0.1). The frequency index was 
likewise normalized, and the severity 
index was intrinsically normalized be- 
cause it is derived by dividing the total 
index by the frequency index. 

The interdependent nature of these 
three indices calls for special consider- 
ations when interpreting the findings. 
Since any one of the indices is mathemat- 
ically determined by the other two, the 
indices should be considered as a set 
rather than individually. For instance, 
a high total index may correspond to high 
severity (a few long absences), to high 
frequency (many short absences), or to 
intermediate values of both severity and 
frequency. The highest severity score 
was for a miner who had one absence in- 
cident that lasted the entire duration of 
the study, resulting in a severity score 
of 242, a total of 242, and a frequency 
of 1/242. Conversely, the highest at- 
tainable frequency index would be approx- 
imately 0.5, indicating a miner who was 
absent every other day. In practice, the 
maximum frequency ranged from 0.07 (in- 
voluntary frequency) to 0.10 (voluntary 
frequency). 

The impact of individual variables was 
assessed using Pearson correlations for 
interval scale variables and one-way 
analyses of variance for nominal vari- 
ables. The correlations are shown in 
table 4. 

Perceived Ability To Attend 

Miners' perceived ability to attend 
work was not directly assessed. Rather, 
its precursors, transportation problems, 
age and illness, and safety, were used in 
predicting actual attendance. 



23 

TABLE 3. - Operational definitions of independent variables 

Variable name Operational definition 

Total absences Number of absences/number of days employed. 

Frequency of absences Number of absence incidents/number of days 

employed. 

Severity of absences Number of absences/number of absence incidents. 

Attendance motivation Not measured. 

Perceived ability to attend Not measured. 

Health status Miner's age, used as surrogate. Computed from 

birthdate from mine records based on date of 
interview. 

Job safety Miner ' s section used as surrogate. 

Satisfaction with safety Interview: "How satisfied or dissatisfied are 

you with the safety of working at this mine?" 

Satisfaction with coworkers Interview: "How satisfied or dissatisfied are 

you with the other members of your crew?" 

Satisfaction with equipment Interview: "How satisfied or dissatisfied are 

you with the quality of the equipment you work 
with?" 

Satisfaction with working Interview: "How satisfied or dissatisfied are 

conditions. you with the bath house, parking area, and 

other facilities above ground [and] the 
physical conditions below ground (e.g., top 
and bottom, water, eating areas)?" 

Satisfaction with opportunities for Interview: "How satisfied or dissatisfied are 
family and social activity. you with the amount of time you have to spend 

with your family and friends?" 

Satisfaction with career advancement Interview: "Is there some other job at this 
opportunities. mine that you would rather have than your 

present one [and] if yes, how satisfied are 
you with your chances of getting that job 
during the next 6-12 months?" 

Satisfaction with job content Interview: "How satisfied or dissatisfied are 

you with your work as a (regular job)?" 

Satisfaction with closeness of Interview: "How satisfied or dissatisfied are 
supervision. you with your present boss?" 



24 

TABLE 3. - Operational definitions of independent variables—Continued 

Variable name Operational definition 

Satisfaction with fairness of Interview: "How satisfied or dissatisfied are 
supervision. you with your present boss?" 

Satisfaction with pay Interview: "How satisfied or dissatisfied are 

you with the amount of pay you get?" 

Overall job satisfaction Interview: "Overall, putting everything we've 

talked about together, how satisfied are you 
working here?" 

Job involvement Not measured. 

Distributive justice Interview: "How fair do you think the company 

is when they decide whether an absence is 
excused or not excused?" 

Absenteeism control system Interview: Leniency variable based on 

permissiveness. responses to four hypothetical absence 

questions. 

Desire to avoid income loss Interview: "Some people say they need 5 days' 

pay a week in order to get by. Some need 5 
days plus overtime. Others claim they could 
make it on 3 or 4 days' pay. Do you need 5 
days [or] 5 days plus overtime [or] could you 
make it on 3 or 4 days?" 

Local job opportunities Interview: "If you had to find another job 

(perhaps because of a layoff) how long do you 
think it would take?" 

Kinship responsibility.. "How many people (not including yourself) are 

dependent on you for support?" 

Personal work ethic Not measured. 

Attendance norms "If you were absent more days than the 

contract allows, how likely is it that you 
would be criticized by your family; be 
criticized by your crew; be criticized by 
your boss?" 

Transportation problems "About how many miles is it from your home to 

the mine?" 



25 



TABLE 4. - Correlations of independent variables with absenteeism measures 



Independent variables 



Totals 



V 



sv 



IV 



Frequency 



SV 



IV 



Severity 



SV 



IV 



Age 

Control system 

permissiveness 

Distance to mine . 

Management fairness 
Kinship responsibility. . 
Local job opportunities. 
Attendance norms: 

Crew . 

Family 

Satisfaction with — 
Advancement 

opportunities 

Coworkers < 

Equipment 

Fringe benefits 

Job content 

Opportunities for 

social activities..... 

Pay 

Safety 

Supervision 

Working conditions: 

Above ground 

Underground « 

Overall satisfaction... 
Section dummy variable: 

1 

2 

3 



-0.07 

-.06 

.07 

.03 

.01 

2-. 42 

-.02 
-.18 



.10 
-.10 
-.11 
-.09 

.02 

.10 

.13 

1-.25 

.14 

-.15 
1 -.26 
'-.23 

.00 

-.10 

.10 



-0.13 

.19 
.14 

-.06 
.09 

-.08 

.21 
-.15 



-.03 

.05 
-.21 
-.07 
-.07 

-.11 
-.00 
-.05 
-.01 

1 -.22 

'-.28 

-.12 

-.14 
-.09 
1 .23 



2 0.29 

-.16 
.02 
-.01 
-.09 
-.23 

-.16 
-.04 



1 -.29 

-.02 

.03 

.03 

.00 

.12 

-.18 

.08 

.04 

-.09 

.08 

-.15 

.02 

.07 

-.08 



-0.08 

-.01 

.08 

-.05 

-.02 

'-.39 

.03 
-.15 



.02 
-.05 
-.07 
-.10 
-.04 

.07 

.13 

-.20 

1 .22 

-.14 
-.21 
-.19 

.05 

-.05 

.10 



•0.14 

.17 
.14 
.03 
.07 
-.07 

.18 
-.16 



-.10 

.03 

1 -.22 

-.11 

-.07 

-.14 
-.01 
-.07 
-.00 

1 -.23 

2 -. 30 

-.16 

-.14 

-.07 

.21 



-0.07 

'-.24 

.07 
2.35 

.06 
-.20 

-.01 
1-.24 



1 -.22 
-.07 

.09 
1 -.22 

.06 

-.17 
.09 

-.05 
.06 

.01 

.13 

2-. 37 

.00 

-.04 

.03 



0.05 

-.07 
.03 
.20 
.04 
.08 

.02 
-.07 



-.18 
.05 
.07 
.04 
.07 

-.04 

.02 

.15 

2 -. 32 

-.07 

-.10 

.07 

.21 
-.14 
-.07 



-0.14 

.05 
.15 
.12 
.11 
-.11 

.05 
'-.26 



'-.24 

.18 
-.09 
-.15 
-.08 

'-.24 

.02 

-.19 

.08 

1 -.2l 
-.10 
-.03 

'-.22 
-.07 
'.29 



: 0.26 

-.04 
-.11 
-.06 
-.14 
-.16 

-.11 
.00 



.13 
.02 
.05 
.05 
.00 

.13 
•.20 

.08 
•.00 

.00 

.07 

-.07 

-.06 

.19 

-.12 



V Voluntary absence. SV Semi voluntary absence. IV Involuntary absence, 
'p < 0.05. 2 p < o.Ol. 



Transportation Problems 

This variable was operationalized in 
terms of the distance miners reported 
they had to drive to work. This opera- 
tionalization was based on the reasoning 
that weather and car problems would be 
more likely to impede miners who had 
greater commuting distances. Although 
there was considerable variation in this 
variable (ranging from 4 to 107 miles 
with a mean of 21 miles), it did not 
directly correlate with any of the nine 
absenteeism variables. As an alternative 
operationalization, ZIP Codes for miners' 
home addresses were obtained from the 
mine records. We used the ZIP Codes 
as a surrogate variable to represent 



variations in accessibility between dif- 
ferent areas. For instance, an area may 
be relatively close to the mine but have 
poor access roads that are occasionally 
impassible. Using ZIP Code as a cate- 
gorical variable, a one-way analysis of 
variance was performed to determine if 
attendance differed significantly from 
one area to the next. However, of the 
nine attendance variables only voluntary 
frequency was reliably predicted by dif- 
ferences between ZIP Code groups. This 
analysis may have been overly conserva- 
tive because there were a relatively 
large number of reported ZIP Codes (24), 
some of which only had one miner but all 
of which substantially limited the power 
of the statistical tests. 



26 



Miners were also asked how many of 
their absences were caused by transpor- 
tation problems. Since the available 
responses were a fixed-choice set of 
relative amounts ("all," "most," "some," 
or "none"), it was not really valid to 
use their answers as a measure of 
absolute levels of the transportation 
problems variable. 

Age and Illness 

Miners' age was significantly corre- 
lated only with involuntary absences, and 
then only with the total and severity 
indices (not with frequency). This makes 
sense in light of our use of the age 
variable as a surrogate for miners ' 
health status: We expected less healthy 
miners to have more lengthy ("severe") 
absences than their healthy counterparts, 
but that their frequency of absence in- 
cidents would not necessarily differ from 
that of healthier miners. 

Safety 

Safety was not directly measured in 
this study, so the miners' working areas 
were used as a surrogate variable that 
would reflect different levels of hazard 
exposure. The miners in this study 
worked in two producing sections and a 
third group worked in the outby areas. 
In comparing the miners in the two pro- 
ducing sections, no significant differ- 
ences in absence rates were found. Be- 
cause the types of tasks performed by 
miners in outby areas are substantially 
different than the tasks performed by 
those who work in producing sections, it 
is not considered appropriate to compare 
them to miners in the two producing sec- 
tions. Any differences in absence rates 
between outby workers and workers at the 
face could be attributed to many factors 
other than differences in the safety of 
their work environment. 

It is recommended that future studies 
use a more direct measure of safety. Ac- 
cident rates or observation of hazards 
are common measures, but they were beyond 
the scope of the current study. 



Attendance Motivation 

Attendance motivation was indirectly 
operationalized as a function of its pre- 
cursor variables. Therefore, the discus- 
sion of findings for these variables will 
examine their relationships with the nine 
absenteeism variables. 

Overall Job Satisfaction 

It was hypothesized that overall job 
satisfaction would have, at best, only a 
minor effect on attendance. As it turned 
out, though, overall satisfaction had a 
significant negative correlation with 
both the total number of voluntary ab- 
sences (r = -0.23, p = 0.034) and the 
frequency of involuntary absences (r = 
-0.37, p = 0.002) absences. Working 
backward, we expected that overall satis- 
faction would depend on miners' levels of 
satisfaction with several specific as- 
pects of their jobs. To test this hy- 
pothesis, an ordinary least squares lin- 
ear regression was performed, using the 
specific satisfaction variables to pre- 
dict variance in overall satisfaction. 
While the derived model accounted for a 
reasonable 33 pet of the variance, this 
did not quite reach conventional levels 
of significance (F = 2.00, p = 0.07). 
The relationships of specific satisfac- 
tion variables with overall satisfaction 
will be discussed below. 

Satisfaction With Safety 

Actual job safety and miners' fears of 
underground hazards were hypothesized to 
affect their satisfaction with the safety 
of their jobs. The fear variable was not 
measured, and only a surrogate was avail- 
able to assess actual safety: the sec- 
tion (work area) variable discussed be- 
fore as a determinant of perceived 
ability to attend. A one-way analysis of 
variance, however, revealed no differ- 
ences between sections in their levels of 
satisfaction with safety. This is con- 
sistent with our earlier interpretation 
that there were probably no real differ- 
ences in safety between the sections. 



27 



Hence, for the subject mine, section is 
probably not a useful surrogate for safe- 
ty. Satisfaction with safety did, how- 
ever, significantly correlate with both 
overall satisfaction and the number of 
voluntary absences. 

Satisfaction With Coworkers 

Miners' satisfaction with the other 
members of their crew was not signifi- 
cantly related to either overall satis- 
faction or any of the absenteeism in- 
dices. It is important to note here that 
the variance on this measure was ex- 
tremely low. Almost all (98 pet) of the 
miners reported that they were either 
satisfied or very satisfied with their 
coworkers. 

Satisfaction With Equipment 

There was more variance on this vari- 
able than on most of the other measures 
of satisfaction. Consequently, it had a 
greater opportunity to explain variance 
in the criteria variables. However, it 
was not significantly related to overall 
satisfaction and significantly predicted 
only the frequency of semi voluntary 
absences. 

Satisfaction With Opportunities For 
Family-Social Activities 

This variable was found to have a sig- 
nificant positive relationship to overall 
satisfaction and was negatively asso- 
ciated with the absenteeism index of 
semivoluntary severity. As predicted, it 
varied significantly as a function of 
shift; night shift miners reported the 
lowest levels of satisfaction (one-way 
analysis of variance, F = 3. 69, p = 
0.03), while day and evening shift miners 
reported almost identical satisfaction 
levels. 



negative correlations with the total and 
frequency Indices of semivoluntary ab- 
sences. Semivoluntary absences tend to 
be the most costly to the miner because 
they are unpaid and can result in disci- 
plinary action. It seems reasonable that 
feelings that work is unpleasant would 
drive miners to take more of these costly 
absences. 

Satisfaction With Job Content 

This variable had small, but signifi- 
cant, correlations with overall satisfac- 
tion. However, it was not significantly 
related to any of the absenteeism 
measures. 

Satisfaction With Supervision 

This variable did not significantly 
correlate with overall satisfaction, but 
it was negatively related to the severity 
of voluntary absences and positively re- 
lated to voluntary absence frequency. 
The strongest relationship here is the 
negative correlation with severity (r = 
-0.34), which indicates that the weaker 
correlation to frequency is probably an 
artifact of the inverse mathematical 
relationship between the two indices. 

Satisfaction With Career Advancement 
Opportunities 

Although miners satisfaction with ad- 
vancement opportunities was not related 
to overall satisfaction, it was nega- 
tively correlated with the total and fre- 
quency indices of involuntary absences as 
well as with the severity of semivolun- 
tary absences. Since promotions could be 
contingent upon good attendance, the 
direction of causality in these relation- 
ships is not clear. 

Job Involvement 



Satisfaction With Conditions of Work 

The two measures of this variable were 
not significantly related to overall sat- 
isfaction, but they both had significant 



This variable was not measured, so its 
components (satisfaction with advancement 
opportunities, job content, and super- 
vision) will be used in its place in the 
overall model. 



28 



Distributive Justice 

Distributive justice usually refers to 
pay equity and the fairness of other non- 
economic reward systems. We used miners' 
opinions of the fairness of the mine's 
absence categorization process as a par- 
tial and imperfect measure of this con- 
struct. This variable had a highly 
significant positive relationship to the 
frequency of involuntary absences. The 
hypothesized determinants of distributive 
justice (satisfaction with pay and super- 
vision) were entered in a regression 
equation to assess their impact. How- 
ever, the 35 pet of variance in the 
criterion variable predicted by this 
model was not significant (F = 2.48, p = 
0.07). 

Absence Control System Permissiveness 

A Guttman scale variable was construc- 
ted on the basis of four questions that 
assessed miners' opinions of whether a 
hypothetical absence would be excused 
under different circumstances. The 
direness of the excuses for absence 
decreased from the first question to the 
last, so miners who said that they would 
be excused on the fourth question re- 
ceived the highest lenience score, while 
miners who said that they would not be 
excused under any of the described 
conditions received the lowest score. 

Scores on the lenience scale correlated 
significantly with only the involuntary 
frequency index. The relationship be- 
tween the four questions that comprised 
the lenience variable and the nine absen- 
teeism variables was examined in detail 
to determine whether a relationship 
existed that was examined in detail to 
determine whether a relationship existed 
that was missed by the summary variable. 
Thirty-six one-way analyses of variance 
(four questions by nine absence measures) 
turned up only three significant rela- 
tionships. Miners who felt that they 
would not be excused for an illness with- 
out a written excuse from a doctor had 
involuntary absences 9 pet of the time, 
while other miners who thought they would 
be excused under the same circumstances 
had an average involuntary absence index 



of only 3 pet. One way to interpret this 
finding is that miners who took more 
"sick, days" (the main type of involuntary 
absence) would be more likely to have 
difficulty getting additional illnesses 
excused. A question about the mine's 
permissiveness for absences due to per- 
sonal reasons showed that miners had 
slightly but significantly more frequent 
involuntary absences if they felt they 
would not be excused for these absences. 
Again, it is possible that the causal 
direction is the reverse of that indi- 
cated in the model: Miners' absence 
history can affect their expectations of 
how they will be treated in the future. 
These results should be taken with a 
grain of salt, however. One or two of 
the 36 analyses of variance could be 
expected to be significant just by chance 
even if no real relationship existed. 

Desire To Avoid Loss of Income 

Local Unemployment Rate 

Since this was a one-mine study, no 
real variation existed in local unemploy- 
ment rate. This variable is still con- 
sidered important to the model, but it 
was not measured in the current study. 

Kinship Responsibility 

Miners were hypothesized to have 
stronger kinship responsibilities as the 
number of dependents they had increased. 
However, this variable did not have a 
significant impact on measured absen- 
teeism. 

Attendance Norms 

Norm-based sanctions were hypothesized 
to affect attendance behavior. Miners 
who felt that criticism from their fam- 
ilies would result from their absences 
had significantly less frequent involun- 
tary absence and lower severity semi- 
voluntary absences. Norm sanctions from 
coworkers and foremen appeared to be less 
influential than family norms since 
neither of these questions significantly 
correlated with absenteeism. 



29 



Personal Values 

Miners' beliefs about work ethic con- 
cepts were not measured. Usually, per- 
sonal values are culturally based, and 
the culture in this one-mine study was 
expected to be too homogeneous to result 
in useful variance in work values. 

ENTIRE MULTIVARIATE ABSENTEEISM MODEL 

The relationships represented in the 
entire model depicted in figure 1 were 
tested by performing a series of large 
multiple linear regressions of all pre- 
dictive variables on the nine absenteeism 
indices. If a summarizing construct was 
measured (e.g., overall satisfaction), 
the percursor variables (satisfaction 
with safety, satisfaction with coworkers, 
etc. ) for that construct were not in- 
cluded in the analysis. Consequently, 
the regressions consisted of 16 indepen- 
dent variables. Because of missing 
values, only 33 cases were complete 
enough for the analyses. This, combined 
with the relatively large number of var- 
iables, reduced the power of the analysis 
to detect meaningful differences. That 
is, the effects of the variables would 
have to be relatively large and free of 
"noise" to result in significantly large 
regression statistics. Attempts to 
increase the statistical power of 
the analysis by selectively dropping 



variables did not substantially improve 
the level of significance, so the entire 
model was retained. The entire regres- 
sion model is listed below: 

Absenteeism = distance to mine + age + 
section 1 dummy + section 2 dummy + S/W 
(Satisfaction with) opportunities for 
social activities + overall job satisfac- 
tion + S/W advancement opportunities + 
S/W Job content + S/W supervision + S/W 
pay + S/W fringe benefits + S/W super- 
vision fairness + control system per- 
missiveness + desire to avoid income 
loss + family norms + crew norms. 

As can be seen from table 5, the re- 
gression equations did explain a sizable 
amount of variance in absenteeism with 
explained variance (regression R 2 ) rang- 
ing from 0.44 to 0.79. However, only one 
of the nine regressions reached the 
conventional 0.05 level of statistical 
significance. The largest proportion of 
explained variance was obtained for the 
regression on voluntary absence severity 
(p=0. 007). Particularly influential 
independent variables in this model were 
satisfaction with pay and satisfac- 
tion with supervision (both surrogates 
for distributive justice). Three other 
models had high levels of explained 
variance that approached, but did not 
attain, statistical significance. 



DISCUSSION 



The overall empirical support for the 
model proposed in this study is not 
overly impressive. However, the failure 
to find empirical support for many of the 
hypothesized relationships between vari- 
ables does not necessarily mean that the 
relationships do not exist. There are 
many reasons (discussed later in this 
section) why the present study could have 
failed to find empirical support for 
hypothesized relationships that do, in 
fact, exist. However, the converse is 
not true. If no relationship actually 
exists, it is unlikely that the present 
study would have come up with empirical 
evidence that suggests that it does. 
Therefore, the fact that some of the 



variables were found to be statistically 
significant predictors of absenteeism is 
quite noteworthy. The implications of 
two such findings are discussed below. 

The regressions that tested the ability 
of the overall model to predict absence 
rates are the most informative. Recall 
that the overall model used to predict 
voluntary absence severity was statisti- 
cally significant. Also recall that the 
variables satisfaction with pay and sat- 
isfaction with supervision were nega- 
tively related to the absenteeism index 
for the severity of voluntary absences, 
and that this index refers to the length 
of absences concerning which miners have 
the greatest discretion — the time allowed 



30 



TABLE 5. - Regression models of nine absenteeism variables 



Independent variables 



Totals 



SV 



IV 



Frequency 



SV 



IV 



Severity 



SV 



IV 



Age 

Control system 

permissiveness 

Desire to avoid income loss 

Distance to mine 

Management fairness 

Attendance norms: 

Crew 

Family 

Satisfaction with — 
Opportunities for 

social activities 

Advancement 

opportunities 

Job content 

Supervision 

Pay 

Fringe benefits 

Overall satisfaction 

Section dummy variables: 

1 

2... 

Variance explained (R 2 ).. . . 



-0.40 

.10 
-.19 

.10 
-.27 

.19 
-.19 



.34 

.03 
.36 
.32 
.23 
.29 
.19 

.47 
.22 



■0.27 

.10 
-.02 

.12 
-.27 

.47 
-.55 



.02 

.08 
.30 
.04 
.18 
.03 
.47 

-.49 
.29 



0.42 

-.15 
-.05 
-.07 
-.05 

-.14 
.07 



-.06 

-.41 
.06 

-.14 

-.42 
.03 

-.18 

.17 
-.10 



-0.39 

.19 
-.08 

.17 
-.21 

.14 
-.15 



.35 

.20 

-.33 

.53 

.35 

-.21 

-.25 

.32 
.22 



.53 



.48 



.56 



.70 



-0.27 

.12 
-.06 

.13 
-.21 

.40 
-.52 



.02 

-.13 
.32 
.03 
.17 
.02 

-.46 

-.52 
-.29 



.44 



0.27 

-.37 
.11 

-.45 
.16 

.07 
-.45 



-.15 

-.30 

-.06 

.16 

.08 

-.11 

.05 

-.32 
.10 



.53 



0.13 

-.05 

-.08 

-.11 

.03 

.04 
.07 



.11 

-.18 
-.14 
-.77 
-.31 
-.05 
.22 

.38 

.04 



.79 



-0.11 

.00 

.37 

-.18 

-.15 

-.04 
-.39 



-.21 

-.38 

.19 

.15 

.07 

-.22 

-.18 

-.77 
-.55 



.67 



0.26 

-.06 
-.07 

.01 
-.15 

-.04 
.15 



.03 

-.43 
.08 

-.19 

-.56 
.05 

-.19 

.28 
.02 



.70 



Voluntary absence. SV Semivoluntary absence. IV Involuntary absence, 
p < 0.09. 2p < 0.01. 



for vacations and personal days. This 
means that, when they had a choice, min- 
ers who were less satisfied, with their 
pay and their supervision were inclined 
to stay away from work longer than those 
who were more satisfied with their pay 
and supervision. 

These findings suggest that miners' 
perceptions about the inequity of the ex- 
change relationship they have with their 
employer are an important determinant of 
absence severity. Inequity theory states 
that employees' judgments about the fair- 
ness of their employer-employee relation- 
ship are largely determined by (1) the 
perceived adequacy of the economic re- 
wards (pay) they receive and (2) the 
degree to which their supervisor is per- 
ceived to be fair. Employees may view 
their supervisor as unfair because the 
supervisor makes unreasonable demands, 
does not give them the recognition they 
deserve, is too critical, or takes 
advantage of them in some way. Inequity 



theory states that feelings of inequity 
are aversive, and people tend to avoid 
participating in exchanges that cause 
such feelings. Under conditions of high 
unemployment, miners may not be able to 
totally withdraw from the exchange, i.e., 
quit. Under such conditions, the only 
viable strategy for reducing inequity 
may be to stay away from work whenever 
possible. 

In summary, the statistically signifi- 
cant findings from this study appear to 
be in line with the predictions of the 
model that were derived from inequity 
theory. This study found that miners who 
are dissatisfied with their pay and/or 
their supervisor tend to be absent for 
relatively long spells. These long 
spells of absence may stem from a reluc- 
tance to resume participating in an ex- 
change that, because it is perceived as 
unfair, tends to cause feelings of anger 
and frustration. When employees who hold 
such views are away from work, they may 



31 



experience temporary relief from these 
noxious feelings. Because returning to 
work is associated with an intensifica- 
tion of these unpleasant feelings, these 
employees may tend to stay away from work 
for relatively long periods. 

The explanation offered above regarding 
dissatisfaction with one's supervisor as- 
sumes that employees' absences are 
prompted by unfair treatment. However, 
an alternative explanation for the ob- 
served relationship is that employees who 
are absent for relatively long spells 
prompt their supervisors to do things 
that result in feelings of unfair treat- 
ment. Given the design used in this 
study, it is not possible to rule out 
this alternative explanation. However, 
based on prior research, the model as- 
sumes that the predominant direction of 
causality is 

perceived unfair treatment * absences. 

Limitations . — It is impossible to per- 
form a completely accurate and comprehen- 
sive test of a model in any one study. 
As in all studies, the methods used to 
test the model proposed in this study had 
certain limitations. First, it was not 
feasible to test all aspects of this 
model. Some variables were not measured 
at all, i.e. , overall attendance motiva- 
tion, perceived ability to attend, job 
involvement, distributive justice, and 
personal work ethic. There is good 
reason to expect that these variables 
have an important influence on miners' 
attendance. However, given various limi- 
tations such as the amount of time that 
could be spent in interviewing each min- 
er, it was impossible to collect all of 
the information needed to test the entire 
model. It is strongly recommended that 
the impact of these variables be assessed 
in future studies of miners' attendance. 

Certain variables in the model can be 
assessed only in studies that involve a 
number of different mines. The present 
study looked at only one mine. There- 
fore, it was not possible to test the im- 
pact that differences in absenteeism con- 
trol system permissiveness or local job 
opportunities have on absenteeism. Such 
variables cannot be tested in studies of 



a single mine because, for the miners who 
work at a single mine site, there are no 
substantial differences in these vari- 
ables. Nevertheless, several studies 
suggest that such variables are important 
determinants of absenteeism. 

The way that the variables in the model 
were operationalized for this study rep- 
resents only one of several approaches. 
One reason for failing to observe signif- 
icant relationships between variables (in 
this or any study) is that the variables 
were not operationalized in a way that 
adequately reflects the concept that one 
hoped to measure. It is always possible 
that certain variables were not opera- 
tionalized adequately, and that if they 
had been operationalized in a better way, 
the data would have supported the model's 
predictions. 

Some variables were assessed using sur- 
rogate measures — ones thought to be high- 
ly correlated with the variable of pri- 
mary interest. For example, age was used 
as a surrogate for the individual's 
health status. Although surrogates pro- 
vide a useful means for testing hypothe- 
sized relationships, they are valid only 
to the extent that they actually do cor- 
relate well with the variable of primary 
interest. The surrogate variables used 
in this study were selected to be the 
best available correlates of the miss- 
ing variables as well as being rela- 
tively unconfounded by other influential 
variables. 

Another limitation to the present 
study's test of the proposed model stems 
from the poor economic conditions that 
existed in the mining industry at the 
time this study was conducted. As pre- 
viously discussed, various studies have 
indicated that absenteeism levels are 
usually significantly lower during times 
of high unemployment. The fact that a 
major layoff occurred at the mine just 
prior to the period during which data 
were collected for this study suggests 
that the levels of absenteeism observed 
were somewhat lower than usual, and that 
the overall amount of variation in levels 
of absenteeism between miners in this 
study was less than usual. 

This has important implications for the 
tests that were performed. The general 



32 



approach to empirically demonstrating 
that two variables are related to one 
another is to show that variations in one 
variable are useful for making predic- 
tions about the other variable — useful in 
the sense that the predictions are more 
accurate than random guessing. Given the 
nature of the mathematics involved, it is 
relatively difficult to demonstrate that 
a "statistically significant" relation- 
ship exists between any two variables if 
one observes very little variation in one 
or both of the variables. 

Because the amount of variation between 
miners' levels of absenteeism was proba- 
bly lower than usual, the present study's 
tests of the proposed relationships be- 
tween variables in the model are on the 
conservative side. If the study had been 
performed when the economy was better and 
there were greater variations in miners' 
absenteeism rates, one would have 
been more apt to find statistically 



significant relationships between the 
variables in the model. 

One must be cautious about generalizing 
these findings to other mines. In 
judging how safe it is to assume that the 
findings from this study are applicable 
to other mines, one should be especially 
careful to take note of differences in 
local unemployment levels, absence con- 
trol policy, and cultural influences. 
One should keep in mind that the less 
similar other mines are to the one ex- 
amined for this study, the less confident 
one can be that the same relationships 
hold true. 

This report has attempted to summarize 
what is known about the causes of miners' 
absenteeism and has not attempted to pro- 
vide the mining industry with advice on 
how to achieve low levels of absenteeism. 
The production of a report addressing 
this issue is currently underway. 



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34 



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48. Locke, E. The Nature and Causes 
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Vancouver, BC, 1983, pp. 214-222. 

51. Miner, J. B., and J. F. Brewer. 
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52. Mobley, W. H. Employee Turnover: 
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53. Moch, M. , and D. Fitzgibbons. The 
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58. Oberman, S., and G. Rainer. Ef- 
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60. Paringer, L. Women and Absentee- 
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61. Patchen, M. Participation, 
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Prentice-Hall, 1970, 289 pp. 

62. Pearce, J. , and R. Peters. 
A Contradictory Norms View of 



35 



Employer-Employee Exchange. J. Manage- 
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65. Porter, L. , and R. Steers. Or- 
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36 



APPENDIX. —INTERVIEW GUIDE FOR MINERS 



February 19, 1986 



Name of Interviewer 



Name of Interviewee 



Date Shift: Day Eve. 



Mine Section 



Robert Peters and Robert Randolph 
U. S. Bureau of Mines 
Pittsburgh Research Center 
Pittsburgh, PA 15236 



37 



INTRODUCTION TO QUESTIONNAIRE 



Hello, my name is . I'm part of the group from the Bureau of Mines in 

Pittsburgh that is spending a few days at the xxxx mine interviewing miners. You may 
have already heard about us from the letter that has been posted at xxxxxx during the 
past week. Briefly what it said is that both the union and management has given us 
permission to talk with you. 

One of the main reasons the Bureau of Mines is doing this study is to find out more 
about why miners are sometimes absent from work. Miners who must temporarily fill in 
for the regular members of an underground mining crew are sometimes unfamiliar with 
the physical conditions of the crew's section and the habits of the people who work 
in the crew. Because temporary replacements are not as familiar with the crew and 
the section, they sometimes either do things or fail to do things that can reduce 
productivity and contribute to accidents. Therefore, the Bureau of Mines is trying 
to find out more about why miners are absent, and what can be done to keep attendance 
at a high level. 

During this interview, I'm going to ask for your opinions about the reasons miners 
are sometimes absent, your feelings about your work, and what you think influences 
safety and productivity at this mine. Most of the questions will probably be quite 
easy to answer, although a few may be more difficult. 

Your participation is completely voluntary. You need not answer every question. 
Anything that you do tell us will be held in strict confidence. By that I mean that 
neither the company nor the union can have this interview, and nothing that you say 
will be identified with you. We will only provide back summary information. For 
example, we might report that 70% of the miners believe that their boss treats them 
fairly. 

We have conducted interviews with miners before and found that most enjoy talking 
about their work. Sometimes their ideas led to improvements at the work site. 

At this point, do you have any questions? 



38 

1. JOB HISTORY 

I'd like to start by getting some information about your experience as a miner. 

1.1. What is your present job? 



1.2. How long have you been on that job? 



1.3. Is that the job you are doing today? Yes No 

(Probe: If "No" ask, "What job are you doing today?") 

1.4. How long have you worked at this mine? 



1.5. Altogether, how many years have you worked as a coal miner? years 



2. WORK SATISFACTION 

My next set of questions concerns how satisfied you are with various aspects of your 
job. What I will do is read you a set of statements. For each statement, I want you 
to tell me how satisfied or dissatisfied you are. 

How satisfied or dissatisfied are you with: 

2.1. The amount of pay you get. 

2.2. The fringe benefits you receive. 

2.3. The amount of job security that you now have. 

2.4. The quality of the equipment you work with. 

2.5. Is there some other job at this mine that you would rather have than your 
present one? 

Yes No [Go to 2.7] 



2.6. If yes, how satisfied are you with your chances of getting that job 

during the next 6-12 months? 

2. 7. The training you received for your present job. 

2.8. Your present boss. 

2.9. The bath house, parking area, and other facilities aboveground. 

2.10. The physical conditions below ground (e.g., top and bottom, water, 

eating areas). 

2.11. (If miner presently holds a temporary job), how satisfied are you with 

your job as a ? 



39 

2.12. Your work as a (regular job). 

2.13. The other members of your crew. 

2. 14. The safety of working at this mine. 

2. 15. The amount of time you have to spend with your family and friends. 

2.16. Overall, putting everything we've talked about together, how satisfied 

are you working here? 

2.17. Is there anything that could be done to make working here more satisfying? 

3. PROBABILITY OF BEING LAID OFF 

As you probably know, miners are sometimes laid off for a variety of reasons — partic- 
ularly when there is a drop in the demand for coal. In the next few questions, I am 
going to ask you about layoffs at this mine. 

3. 1. Do you think any miners at this mine will be laid off (not fired) within the 
next year? 

Yes No (skip to amount of search) 



3.2. How likely is it that you will be one of the miners laid off in the next year? 

4. AMOUNT OF SEARCH 

4. 1. Have you thought about finding a different job away from this mine? 
Yes No 

4.2. Have you spent any time looking for another job in the past year? 
Yes No 

5. JOB OPPORTUNITIES 

5. 1. If you had to find another job (perhaps because of a layoff) how long do you 
think it would take? 

days 



40 

6. ABSENTEEISM QUESTIONS 

6.1. Some people say they need 5 days' pay a week in order to get by. Some need 
5 days plus overtime. Others claim they could make it on 3 or 4 days' pay. 
Do you need: 

5 days 5 days plus overtime Could make it on 3 or 4 days 

6.2. MINERS' OWN PAST ABSENCES 

6. 2. 1. Think back to the last day you missed work for any reason. About how long 
ago was that? 



6.2.2. Why did you take that day off? 

6.2.3. When did you decide when you were going to take that day off? 

On that day The day or so before More than a couple of days 

before 

6.2.4. Was it unusual for you to miss work because of (reason)? 

Yes No (skip to next question) 

In what way was it unusual? 

6. 2. 5. You said that you were absent because of . How much control 

did you have over the things that caused you to be absent? 

6. 2. 6. Under the current contract, there are nine personal days and floating days 

that can be taken off. Some people take all of those days off, others take 

only some of those days off, and others take off none of those days. In this 

year, are you going to take all of them, some of them, or none of them off? 
(Circle one) 

All Some None 

The next set of questions concerns various reasons why a miner might be absent from 
work. What I'd like you to do is consider all of the times you were absent over the 
past year or two. 

For example, let us consider accidents, either on or off the job. If you had no ab- 
sences during the last year or two due to an accident, then you should indicate "4, 
not an important" cause. 

On the other hand, it's possible that virtually all of your absences during the past 
year or two were caused by accidents. If that were the case, then you should indi- 
cate "1, a very important" cause. 

The answers "important," and "slightly important" should be used to indicate in- 
between levels. 



6. 


2. 
2. 
2. 
2. 

2. 
2. 


7. 


6. 


8. 


6. 


9. 


6. 


10. 


6. 


11. 


6. 


12. 



41 



Accident, either on or off the job 

Personal illness 

Family illness 

Legal or financial problems that need to be resolved during working 
hours. 

Too hungover to work 

Transportation problems 

O.K. we've got about 6 more to do. 

6.2.13. Family or marital problems 

6. 2. 14. Problems with your house or property 

6.2.15. Wanting to go hunting or fishing 

6.2.16. Being with your family 

6.2.17. Just being by yourself for a day 

6.2.18. Working on a hobby 

If you were absent more days than the contract allows, how likely is it that you 
would: 

6.2.19. be criticized by your family 

6. 2. 20. be criticized by your crew 

6.2.21. be criticized by your boss 

6. 2. 22. Thinking about all of the reasons why you have been absent, how much control 
do you have over whether you are absent or not? 

6.3. MINERS' OWN FUTURE AND HYPOTHETICAL ABSENCES 

6.3.1. Let's assume that you used up all your contract days and then took off be- 
cause you were ill. If you did not have a doctor's slip, is it likely that 
the company 

a. would excuse you? 



b. would not excuse you? 

(If response is "it depends," check here and ask, "you said it 

depends... on what does it depend?") 



42 

6.3.2. Let's assume that you used up all your contract days and then took off be- 
cause of an Illness In your family . If you did not have a doctor's slip or a 
hospital excuse, is it likely that the company 

a. would excuse you? 

b. would not excuse you? 

(If response is "it depends," check here and ask, "you said it 

depends... on what does it depend?") 

6.3.3. Let's assume that you used up all your contract days and then took off be- 
cause of personal business , e.g. , your furnace broke down or you had to go to 
the bank. If you notified them in advance, is it likely that the company 

a. would excuse you? 

b. would not excuse you? 

(If response is "it depends," check here and ask, "you said it 

depends... on what does it depend?") 

6.3.4. If you did not notify them in advance, is it likely that the company 

a. would excuse you? 

b. would not excuse you? 

(If response is "it depends," check here and ask, "you said it 

depends... on what does it depend?") 

6.3.5. How fair do you think the company is when they decide whether an absence is 
excused or not excused? 

6.4. OTHER MINERS' ABSENCES 

I'm going to ask a set of questions concerning various reasons why a miner might be 
absent from work. What I'd like you to do this time is consider all of the times you 
can remember when other miners at this mine were absent over the past year or two. 

We'll be using the importance card again, so the instructions are the same. 

6.4.1. Accident, either on or off the job 

6.4.2. Personal illness 

6.4.3. Family illness 

6.4.4. Legal or financial problems that need to be resolved during working 

hours. 

6.4.5. Too hungover to work 

6.4.6. Transportation problems 



43 



O.K. we've got about 6 more to do. 

6. 4. 7. Family or marital problems 

6.4.8. Problems with their house or property 

6. 4. 9. Wanting to go hunting or fishing 

6.4.10. Being with their families 

6.4.11. Just being by themselves for a day 

6.4.12. Working on a hobby 

6.4.13. Thinking about all of the reasons why other miners here have been absent, 
how much control do they have over whether they are absent or not? 

7. ACCIDENTS AND SAFETY 

The next few questions are about safety and accidents at this mine. I'm going to 
read a list of statements about the reasons for accidents that cause people to be in- 
jured at the xxxxx mine. Using this response card, I'd like you to rate how impor- 
tant each of these reasons is for explaining why miners suffer injuries. 

How important is as a contributor to mining accidents? 

7. 1. faulty or poorly maintained equipment. 

7.2. poorly maintained roof conditions. 

7.3. foremen's lack of interest in safety. 

7. 4. the fact that some miners may fail to realize that certain things they 

do are dangerous. 

7. 5. the fact that some miners may not know how to take care of unsafe 

conditions. 

horseplay and showing off. 

unavoidable "Acts of God or nature. " 



7. 


6. 


7. 


7. 


7. 


8. 


7. 


9. 


7. 


10. 



the fact that some miners may be so worried about their personal pro- 
blems that they don't concentrate on what they are doing. 

the excessive use of drugs or alcohol. 

the fact that miners sometimes try to save time by taking shortcuts 
that could be dangerous. 



44 



7.11. In any mine, and particularly this one, we would like to improve safety by 

reducing accidents. Let's assume when you come to work tomorrow that you 

have all the money and authority you need. What would you do to improve 
safety at this mine? 



8. MAJOR PROBLEMS 

I'm going to read a list of things that are major problems at some mines, but not at 
others. I'd like you to tell me the extent to which you agree or disagree that each 
item is a major problem at this mine. 

8.1. bad roof conditions 

8.2. lack of cooperation between crews 

8.3. too much absenteeism 

8.4. too many accidents 

8.5. poor relations between labor and management 

8.6. poor equipment 

8.7. too much down time 

8.8. Are there any other major problems at this mine? 

8.9. What is the most serious problem this mine faces? 

8.10. I think it's fair to say that the costs of producing a ton of coal are in- 
creasing. The cost gets passed on in our electric bills. Let's assume when 
you come to work tomorrow you have all the money and authority you need. What 
would you do to reduce the costs of producing coal from this mine? 

8.11. What would you do to increase productivity? 

8.12. What would you do to reduce absenteeism? 

8.13. Do you think that any changes should be made at this mine? 



45 



9. BACKGROUND INFORMATION 

We've talked a lot about your work. Now I'd like to finish up by asking you a few 
questions about yourself. 

9. 1. How old are you? years 

9. 2. Are you married? Yes No 

9.3. How many people (not including yourself) are dependent on you for support? 

dependents 

9.4. About how many miles is it from your home to the mine? 

miles 

Finally, do you have any objection to our obtaining additional data about you from 
company personnel files? 

I have no objections. 



U.S. GOVERNMENT PRINTING OFFICE: 1987 605 017/60115 INT.-BU.OF Ml NES,PGH. ,PA. 28578 



U.S. Department of the Interior 
Bureau of Mine*- Prod, and Oiatr. 
Cochrans Mill Road 
P.O. Box 18070 

Pittsburgh, Pa. 15236 



OFFICIALBUSINESS 
PENALTY FOR PRIVATE USE. $300 

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AN EQUAL OPPORTUNITY EMPLOYER 




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